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A Guide to Problem-Solving for Software Developers with Examples

If I ask you, out of the blue, what’s the role of a developer, what would you answer? Coding all day? Drinking coffee? Complaining about the management?

To me, a developer is first and foremost a problem solver, simply because solving problem is the most important (and the most difficult) part of our job. After all, even if our code is perfect, clear, performing great, a masterpiece of form and meaning, it’s useless if it doesn’t solve the problem it was meant to solve.

So, let’s dive into problem-solving today. More specifically, we’ll see in this article:

• How to define a problem, and the difference sometimes made between problem-solving and decision-making.
• Why some problems should not be solved.
• The two wide categories of problems you can encounter.
• Why it’s important to correctly define the problem, and how to do so.
• How to explore the solution space.
• Why deferring a problem might be the best decision to make in specific situations.
• Why reflecting on the whole process afterward can help you in the future.

This article is mostly based on my own experience, even if I apply here some ideas I found in books and papers.

We have our plan. Now, it’s time to dive deep into the difficult, but rewarding, process of problem-solving.

Problem-Solving and Decision-Making

“When I use a word,” Humpty Dumpty said in rather a scornful tone, “it means just what I choose it to mean — neither more nor less.” “The question is,” said Alice, “whether you can make words mean so many different things.” “The question is,” said Humpty Dumpty, “which is to be master — that’s all.” Lewis Caroll Source

Words are ambiguous; they can mean different things for each of us. So let’s first begin to agree on the definition of “problem-solving” here, to be sure we’re on the same page.

Let’s first look at the definition of the word “problem” in a dictionary:

• According to the American Heritage Dictionary , a problem is “a question to be considered, solved, or answered”.
• According to the Oxford Learner’s dictionary , a problem is “a thing that is difficult to deal with or to understand”.

In short, in any problem, there is some degree of uncertainty. If you’re certain of the solution, the problem is already solved. Nothing would need to be “considered, solved, or answered”.

Information is useful to reduce this uncertainty. The quantity is often not the most important, but the quality will be decisive. If I tell you that 90% of my readers are extremely intelligent, would it help you to solve a problem in your daily job? I bet it wouldn’t. It’s information nonetheless, but its usefulness for you is close to zero.

This is an extreme example, but it highlights an important point: before collecting any data, define your problem clearly; then, according to the problem, decide what data you need. Yet, many companies out there begin to collect the data and then decide what problem to solve. We’ll come back to that soon in this article.

So, to summarize, a problem is a situation with some degree of uncertainty. Sometimes, this uncertainty needs to be reduced to come up with an appropriate solution, or, at least, a decision to move forward to your specific goal.

Is there a Problem to Solve?

Whenever you (or somebody else) see a problem, you should always ask yourself this simple question first: is it really a problem, and should we solve it now ?

In other words, ask yourself the following questions:

• Why is this problem important to solve?
• Would be solving the problem creates some value? What value?
• What would happen if the problem was not solved?
• What desired outcome do we expect by solving the problem?

If the problem doesn’t bother anybody and solving it doesn’t create any value, why allocating effort and time to solve it?

It sounds obvious, but it’s an important point nonetheless. More often than not, I see developers heading first in solving problems without asking themselves if they should solve them at the first place.

The most common examples I can think of are useless refactoring. I saw developers refactoring parts of codebases which never change, or is rarely executed at runtime. In the mind of the developer, the code itself is the problem: refactoring is the solution.

I remember a similar case: a developer refactored part of the codebase which was basically never used. We discovered, months later, when we had more and more users using this specific part of the codebase, that the refactoring didn’t really simplify anything. To the contrary; we had to refactor the code again. The first refactoring tried to solve a problem which didn’t exists.

Of course, the developer could argue that the value created is a “cleaner” codebase, but it’s arguable, especially when the code is neither often modified nor used. The value created here is not clear, and it would have been easier if the first refactoring never happened. In this specific situation, I recommend refactoring when you actively change part of the codebase for another reason (implementing a new feature for example).

Whether a problem is worthy to be solved is subjective. It also depends on the problem: if the solution is clear and straightforward, it might be useful to solve it, if the consequences of the solution are also clearly known and the risks are low. Unfortunately, these kinds of problems, in practice, are quite rare.

Types of Problems

I would define here two wide categories of problems: the problems with a (or multiple) clear solution (what the literature call “problem-solving”), and the problems without clear solution (it’s sometimes called “decision-making” instead of “problem-solving”).

In fact, if the problem you’re trying to solve has a clear, accepted answer, it’s very likely it has been solved already. It’s often the case for mechanical, technical problems. For example, let’s say that you need to order a list; you just have to search on the wild Internet how to do so in your programming language of choice, and you’re done! You can ask an “AI” too, or stack overflow, or whatever.

In my experience, most technical problems have one (or multiple) accepted solution. I won’t speak about these kinds of problems at length in this article, since they’re the easiest to solve.

When you’re in front of a problem which has no clear solution (even after doing some research), it’s where things get more complicated. I’d argue that most problems you’ll face, as a software developer, are of this category. Problems which are directly linked to the domain of the company you work with are often specific (because they depend on the domain), and complex.

For example, I’m working for a company providing a learning platform for medical students who want to become doctors, among other services. This context is changing because the real world is changing; medicine is no exception.

Recently, we had to create new data structures for the knowledge we provide; these data structures are directly linked to the domain (medicine) here. But what data structures to create? How can they adapt to the ever-changing environment? How to capture the data in the most meaningful way, with understandable naming for other developers?

Decisions had to be made, and when there are no clear solutions, you need to come up with a couple of hypothesizes. They won’t feel necessary like solutions , but rather decisions to take to move forward toward the desired outcome. It often ends up in compromises, especially if you’re working in a team where the members have different opinions .

Also, architectural decisions have often no clear solutions because they depend, again, on the changing context. How to be sure that an architectural decision is good today and in three months? How can we make the architecture flexible enough to adapt to the blurry future?

As developers, we deal with complex codebases, which are somewhat linked to the even more complex real world. It’s difficult to know beforehand the consequences of our decisions, as well as the benefits, the drawback, and the potential bugs we introduce.

Before jumping into the solution space however, we first need a good detour in the problem space.

Defining the Problem

Correctly stating the problem.

After determining that we indeed have some kind of problem, it’s tempting to try to find a solution directly. Be patient: it’s better to look at the problem more closely first.

If you don’t specify well the problem, you might not solve it entirely. It’s also possible that you end up solving the wrong problem, or the symptoms of a problem, that is, other minor problems created by a root problem. Often, the ideal scenario is to find the root problem, even if you don’t want to tackle it first. In any case, it’s always useful information.

For example, not long ago, our users didn’t find the content they were searching for, using our search functionality on our learning platform.

We could have directly solved the problem by asking the search team to adjust that for us, but this problem was only a symptom. It wasn’t the first time that we had to spend time and energy trying to communicate to the search team what we wanted to fix; the real root problem here was that we didn’t have any ownership of our search results.

The solution: we created a better API communicating with the search team, to be able to adjust ourselves the search results in a more flexible manner.

When looking at a problem, a good first step is to write it down. Don’t do it once; try to find different formulations for the same problem.

Writing is nice (I love it!), but other ways to represent ideas can be really useful too. You can try to draw what you understand from the problem: a drawing, a diagram, or even a picture can help you understand the problem.

From there, you can ask yourself: do you have enough information to take a decision? The answer will be mostly based on the experience of the problem solver, there is no magical formula to be sure that you can and will solve the problem.

You should also try to look at the problem from different angles, to really frame it correctly. The best way to do so is to solve problems as a team.

Solving Problems in a Team

Trying to describe and think about a problem is a great beginning, but it’s even better if you do it as a team. You can exchange experience, opinions, and it’s easier to look at a problem from multiple angles when multiple developers are involved.

First, make sure that everybody in the team is aware of the problem. Defining it altogether is the best. If you have a doubt that somebody is not on the same page, you can re-explain it using different words. It might bring more insights and ideas to the discussion.

Don’t assume that everybody understands the problem equally. Words are powerful, but they are also ambiguous; never hesitate to ask questions (even if they seem stupid at first), and encourage the team to do the same. If your colleagues see that you’re not afraid to ask, it will give them confidence to do the same.

The ambiguity can also build overtime, after the problem was discussed. That’s why it’s really important to document the whole process, for anybody to be able to look at it again and fix the possible creeping misconceptions. Don’t try to describe everything, but try to be specific enough. It’s a delicate balance, and you’ll get better at it with experience.

If you don’t like writing, I’d recommend you to try anyway: this is a powerful skill which will be useful in many areas of your life.

Regarding the team of problem solvers, diversity is important. Diversity of opinion, experience, background, you name it. The more diverse the opinions and ideas are, the more chances you’ll have to solve the problem satisfyingly (more on that later). If the members of the team have enough respect, humility, and know how to listen to their colleagues , you’re in the perfect environment to solve problems.

As developers, we’re dealing with moving systems, because they need to reflect the ever-changing business domain of the company you’re working with. These problems are unique, and even if similar problems might have been solved in the past, they’re never the exactly same. The differences can have an impact on the solution, sometimes insignificant (allowing you to re-apply the solution found previously), sometimes important enough to change the solution entirely.

Exploring the Solution Space

Now that we’ve defined the problem, thought about it with our team, tried to look at it from different angles, it’s time to try to find solutions, or at least to make a decision.

What is a good decision? The one which will bring you closer to your desired outcome. It sounds obvious, but there can be some ego involved in discussions, which will push us to try to be right even if it’s not the best solution in the current context. Our personal incentives can conflict with the company’s best interest; it’s always good to try to stay aware of that.

The solution should also be the simplest possible, while still moving forward to the desired outcome. It should also have an acceptable level of risk when we decide to apply the solution. In my experience, complicated solutions are the ones which come up first: don’t stop there. Take some time trying to find the best solution with your team.

For example, here’s what we do with my actual team:

• We define the problem altogether.
• We try to think about different hypothesizes. Not only one, but a couple of them.
• We write the benefits and drawbacks of each hypothesis (which can lead to more ideas, and possibly more hypothesizes).
• We commit to a hypothesis, which then needs to be implemented.

What I meant by “hypothesis” here is a solution which might work; but only the implementation of the hypothesis can be considered as a solution. Before the implementation, it’s just an informed guess. Many things can go wrong during an implementation.

This process looks simple, but when you have multiple developers involved, it’s not. Again, if each member of the team have good soft skills and some experience, it can be an enjoyable and rewarding process. But you need a good team for it to work efficiently (that’s why it’s so important to ask the good questions when joining a company). It’s even better if the members of the team are used to swim in uncertainty, and take it as a challenge more than a chore.

The process described above is just an example; in practice it’s often more chaotic. For example, even when a decision is made, your brain might still continue to process the problem passively. If you find some flaws in the hypothesis you’ve committed to, congratulations! You have now a brand-new problem.

I can’t emphasize it enough: try to be as detached as possible from your ideas, opinions, and preferred hypothesizes. The goal is not for you to be right and feel good, but for your company to move in the good direction. It’s hard, but with practice it gets easier.

I also want to underline the importance of finding both benefits and drawbacks for the different hypothesizes you (and your team) came up with.

To find good solutions, we might also need to reduce the uncertainty around their possible consequences. Doing some external research can help, like gathering data around the problem and the possible hypothesizes. In the best case scenario, if you can find enough data, and if you feel confident that you can move forward with a hypothesis, that’s already a great victory.

If you don’t have enough external information to reduce the uncertainty to a level you feel comfortable with, look at your past experience. Try to find problems similar to the one your deal with in the present, and try to think about the solutions applied at the time, to see if they could also be applied in your current case. But be careful with this approach: complex problems are context-sensitive, and the context you were in the past will never be exactly the same as the present and future contexts.

For example, I recently changed the way we display search results in our system, because we had some data indicating that some users had difficulties to find what they really wanted to find. The problem: users have difficulties to find the good information; it’s a recurrent problem which might never be 100% solved. That said, thanks to the data gathered, we found an easy way to improve the situation.

The data was very clear and specific, but it’s not always the case. More often than not, your data won’t really prove anything. It might only show correlations without clear causality. It will be even more true if you begin by gathering data without defining first the problem you try to solve. You can find problems looking at some data, that’s true, but it needs care and deep understanding of what you’re doing; looking at data when you know exactly what you want to solve works better.

Using this kind of process, the hypothesis is often some sort of compromise. That’s fine; committing to a hypothesis is not the end of the process, and there will be other occasions to revisit and refine the solution.

If you don’t feel comfortable with the level of uncertainty of the problem (or the risk involved by applying your hypothesis), you need to dig more. Writing a prototype can be useful for example, if you hesitate between two or more approaches. If your prototype is convincing enough, it can also be useful to gather feedback from your users, even if the ones testing your hypothesis will always be more invested if they test a real-life functionality, instead of a prototype which might use dummy data, or be in a context which is too remote from the “real” context.

In my opinion, prototypes are not always useful for complex problems, because a prototype only test a new feature at time T, but doesn’t allow you to see if the solution stay flexible enough overtime. That’s often a big concern: how will the solution evolve?

But prototyping can still help gather information and reduce the uncertainty of the problem, even if the prototype doesn’t really give you the solution on a silver platter. It’s also great for A/B testing, when you’re in the (likely) case when you have not much information about the real needs of your users. You could ask them of course, but nothing guarantee that they know themselves what these needs are.

If you don’t find any satisfying hypothesis to your problem, you might also challenge the desired outcome. Maybe a similar, simplest hypothesis, with slightly different outcomes, could work better? If it makes things easier, faster, and less complex, it could be the best solution. Don’t hesitate to challenge your stakeholders directly on the desired outcomes.

Deferring the Problem

In some cases, you might be hesitant to try to solve a problem if there is still too much uncertainty around it. In that case, it might be best to defer solving the problem altogether.

Deferring the problem means that you don’t solve it now ; you keep things as they are, until you get more information to reduce the uncertainty enough.

We had a problem in the company I worked with some time ago: we have dosages which can be discovered in articles, but users didn’t really find them, and nobody really knew why. Because of this lack of information, the problem was not tackled right away, but differed. From there, data have been collected overtime, allowing us to understand the scope of the problem better.

Don’t forget that deferring a problem is already taking a decision. It might be the less disruptive decision for the application and its codebase, but it’s s decision nonetheless, and it can have consequences. Seeing a differed problem as a decision will push you to think about the possible consequences of your inaction, and you’ll look at it as a partial “solution”, with some uncertainty and risk associated to it.

In my experience, deferring the problem works well only when you try to actively seek more data to solve it later. It can be some monitoring to see how the problem evolves, or some data taken from users’ actions. Sometimes, simply waiting can also give you important information about the nature of the problem.

What you shouldn’t do is try to forget the problem. It might come back in force to haunt your sleepless nightmares later. Avoiding a problem is not deferring it.

Here’s another example: we began recently to build some CMS tooling for medical editors, for them to write and edit content on our learning platform. We had one GraphQL API endpoint at the beginning, providing data to two different part of the application:

• Our CMS for medical editors.
• Our learning platform for medical students.

We knew that using one single GraphQL endpoint for these two types of users could cause some problems.

But we didn’t do anything about it, mostly because we didn’t see any real, concrete problem, at least at first. When a minor symptom, related to this unique endpoint, popped up, we spoke about it, and we still chose not to do anything. We preferred deferring the problem once more, to try to solve the real problem (one API for two different kinds of applications) later.

Finally, when we had enough symptoms and some frustration, we decided to split our graphQL API in two different endpoints. It was the best moment to do so: we had enough information to come up with a good decision, we applied it, and we stayed vigilant, to see how our applied hypothesis would evolve.

Moving fast and breaking things is not always the best solution. In some situations, waiting a bit and see how things evolve can allow you to solve your problems in a more effective way. But, as always, it depends on the problem, its context, and so on.

Reading this article, you might have wondered: how much information is enough to be comfortable enough to apply a solution? Well, again, your experience will be the best judge here. You’ll also need to consider carefully risks, benefits, and drawbacks. It doesn’t mean that you need to chicken out if you don’t have 100% certainty about a problem and some hypothesizes; being a software developer implies to have some courage and accept that mistakes will be made. It’s not an easy task, and there is no general process to follow in any possible case.

In short: use your brain. Even if you’re totally wrong, you’ll have the opportunity to fix the bad decisions you’ve made before the implementation, during the implementation, and even after it. We don’t code in stone.

The Implementation: The Value of Iteration

You’ve gathered with your team, tried to define the problem, found multiple hypothesizes, and agreed to try one of them. Great! Problem solved.

Not so fast! We still need to apply the hypothesis, and hope that it will become a good solution to the problem. Doing so, you’ll gather more information along the way, which might change your perspective on the problem, on your hypothesizes, and can even create some baby problems on its own.

It’s where the agile methodology is useful: since we’ll never have 100% certainty regarding a problem and its possible solution, we’ll learn more about both while implementing the hypothesis. That’s why it’s so valuable to iterate on the implementation: it gives you more information to possibly adjust your code, or even the problem, or even switching hypothesizes altogether. Who knows? A solution which is not implemented is just a guess.

If the hypothesis applied is not the ones you would have personally preferred (compromising, or even giving up on your preferred solution is common in a team), only applying it will tell you if you’re right or wrong; that is, if the hypothesis can become a solution solving the problem, at least in the present context.

If you’re worried about how a specific solution will evolve overtime, it’s more complicated, because an implementation won’t give you the information you seek. Still, implementing a hypothesis can be a great source of learning (the most valuable to me is when I’m wrong, because I learn even more). If you think that your hypothesis can have better outcome at time T, you might also try to implement it and compare it. Again, it’s where prototyping is useful.

When applying the solution, you need to look at the details of the implementation, as well as the big picture, to judge if the solution you’re creating is appropriate (leading to the desired outcome). This is a difficult exercise. In general, a developer should be able to reason on different levels of abstraction, more or less at the same time. Again, if you’re aware of it, your experience will help you here, and you can also push yourself to think of all the possible risks and consequences at different levels.

If you work in a team, try to participate (at least a bit) into the implementation of the solution. It’s not good to create silos in teams (that is, only a couple of members have some information others don’t have).

You can go as far as looking at other projects, and ask yourselves these questions:

• Did we had similar problems on these other projects? How did we solve them?
• What was the context of these projects? Is it similar to our current context?
• What did we learn from these other problems, and their implementation? Is the implementation similar to what we’re doing now?

In any case, I would definitely recommend you to write a development journal. I write mine for years, and it has been valuable in many cases. I basically write in there:

• The interesting problems I had.
• The decisions made.
• How the implementation of the solution evolved overtime.
• The possible mistakes we made along the way.

It’s a great resource when you have a problem and you want to look at your past experience.

To evaluate your decisions overtime, nothing will beat a good monitoring process: logs, tests, and so on. It’s what the book Building Evolutionary Architecture call “fitness functions” for example, some monitoring allowing you to measure how healthy your architecture stays overtime. It doesn’t have to stop to the architecture; you can think about different monitoring system to see how something evolve, especially if the solution has still a lot of uncertainty regarding its benefits, drawbacks, and risks.

You can also do that retrospectively: looking at how the code complexity evolve overtime using Git for example.

Retrospective on the Process

We defined the problem, implemented a solution iteratively, and now the problem is gone. That’s it! We made it! Are we done now?

Decisions are sometimes not optimal, and implementing a solution successfully doesn’t mean that there wasn’t a better (simpler) one to begin with. That’s why it can be beneficial to look back and understand what went right, and what went wrong. For example, we can ask ourselves these questions:

• Looking at what we learned during the whole process, is there a potentially better hypothesis to solve the problem in a simpler, more robust way?
• What are the benefits and drawbacks we missed when speaking about the different hypothesizes, but we discovered during the implementation? Why we didn’t think about them beforehand?
• What other problems did we encounter during the implementation? Did we solve them? Did we differ some? What should be the next steps regarding these new problems?
• What kind of monitoring did we put in place to make sure that the solution won’t have undesired outcomes overtime? Can we learn something with this data?

Reflecting on past solutions is a difficult thing to do. There is no way to logically assess that the decision taken was better than others, since we didn’t implement the other hypothesizes, and we didn’t look at them overtime to appreciate their consequences. But you can still look at the implementation of the solution overtime, and write in your developer journal each time there is a bug which seems directly related to the solution. Would the bugs be the same if another solution would had been applied?

Bugs are often not an option; they will pop up, eventually. Nonetheless, it’s important to make sure that you can fix them in a reasonable amount of time, and that you don’t see them creeping back in the codebase after being solved. Some metrics, from the DevOps movement (like MTTR for example) can help here. Sometimes, bugs will show you a better, more refined solution to the original problem; after all, bugs can also give you some useful information. They are also the most direct result of the implementation of your solution.

If you want to know more about measuring complexity (which can be also used to measure complexity overtime after applying a solution), I wrote a couple of articles on the subject .

Humility in Problem-Solving

It’s time to do a little summary. What did we see in this article?

• We need to ensure that the problem we found is really a problem we need to solve. Is there any value to solve the problem? Is it even a problem?
• Try to determine what kind of problem you have: a problem which can have multiple, specific, known answers (like a technical problem), or a problem which depends on the real-life context, without known solutions?
• Defining the problem is important. Try to define it using different words. Write these definitions down. Does everybody in your team understand the problem equally?
• It’s time to explore the solution space. Draft a couple of hypothesizes, their benefits, drawbacks, and risks. You can also do some prototyping if you think it would give you more information to take the best decision.
• Do you have enough information to implement a hypothesis, becoming effectively a solution? If it’s not the case, it might be better to keep the status quo and try to solve the problem later, when you’ll have more information. But don’t forget the problem!
• If you decide to implement a solution, do it step by step, especially if you’re unsure about the consequences of your decisions. Implement an independent part of the hypothesis, look at the consequences, adjust if necessary, and re-iterate.
• When the solution is implemented, it’s time to reflect on the whole process: did we solve the problem? What other problems did we encounter? Maybe another solution would have been better? Why?

As I was writing above, most problems you’ll encounter will be complex ones, embedded into a changing environment with different moving parts. As a result, it’s difficult to train to solve problems in a vacuum; the only good training I know is solving real life problems. That’s why your experience is so important.

Experience build your intuition, which in turn increase your expertise.

You’ll never have 100% certainty that a solution will bring you the desired outcome, especially if you are in front of a complex problem with a blurry context. If you are absolutely convinced that you have the good solution without even beginning to implement it, I’d advise you to stay humber in front of the Gods of Complexity, or they will show you how little you know.

• How to solve it
• Hammock Driven Development
• When Deferring Decisions Leads to Better Codebases
• Lean Development - deferring decision

Problem-Solving Skills for Software Developers: Why & How to Improve

Problem-solving skills go hand-in-hand with software development. Learn some great problem-solving techniques and tips for improvement here!

Software developer jobs today require that you possess excellent problem-solving skills , and for good reason. Unfortunately, there seems to be a sort of talent gap when it comes to this one skill required of all software developers.

Troubleshooting and problem resolution are both informally and formally taught, but you mostly find that software developers have to learn problem-solving skills on their own. This is true for self-taught developers , obviously, but also even for those with software engineering degrees or who’ve graduated from coding boot camps.

This is why it’s necessary to acquaint yourself with the problem-solving process, whether you are a newbie or an experienced developer. In this article, we’ll explore everything you need to know about problem-solving so you can 10x your software development career.

What are Problem-Solving Skills?

As a developer, what do we mean by problem-solving? Let’s attempt a simple definition.

In software development, problem-solving is the process of using theories and research to find solutions to a problem domain, while testing different ideas and applying best practices to achieve a desired result. Problem-solving also has to do with utilizing creativity and logical thought processes to identify problems and resolve them with software.

Becoming a great software developer hinges more on learning algorithms than programming languages or frameworks . And algorithms are simply step-by-step instructions to solve a given problem.

Read More : How to Build a Software Engineer Portfolio (With Examples & Tips)

Why are impeccable problem-solving skills crucial?

Making good use of a computer language can be likened to being a skilled writer. An effective writer must know how to construct sentences and use grammar appropriately. There’s more to writing than just knowing all the words in the dictionary, and that’s how it works for developers, too.

You have different tasks to work on as a software developer, including perhaps designing, coding, and troubleshooting. Much of your time will be spent on identifying problems, spotting and correcting bugs, and making sense of codebases from before you started working there. Being ingenious at problem-solving is essential in creating incredible solutions to issues that arise throughout software development.

To demonstrate ingenuity, let’s consider Google’s autocomplete tool as an example.

The autocomplete tool is built to suggest related terms in the search bar as you type. The idea behind the tool is to reduce more than 200 years of time spent typing daily and to help users save time by up to 25% while typing.

Here’s what had to be done:

• To activate real-time completion of suggestions, the UI experience and JavaScript had to be implemented.
• Next, since users could type just about anything, the autocomplete suggestions had to be compiled into a sensible list dependent on user input.
• Then, Google had to create a back-end sustainability system for this function. Doing this meant massively increasing its infrastructure to accommodate all forms of data query and HTTP requests.
• Finally, the user interface had to be refined by software engineers in order to make sure that every user enjoyed a worthwhile experience. So they employed Google Trends to power the auto-completion tool while using algorithms to take out explicit or offensive predictions in line with Google’s auto-completion policy.

This is just one of Google’s innumerable problem-solving examples, but it’s clear to see that solving problems involves more than just telling a computer to do stuff. It’s about your ability to come up with parameters rightly tailored to target users so they can meet their goals.

So why must developers focus on problem-solving at work?

Software developers work with a wide range of people and departments, and it’s common to discover that some clients and teams find it difficult to define what they want. As a problem solver, it’s up to you to help them identify their needs and communicate their thoughts in an effective way.

Of course, you’ll need time and practice to develop your problem resolution ability. That’s because it’s less about solving problems faster but more about coming up with the best solution . And then you’ll need to deploy that solution.

Read More : Common Interview Questions for Software Developer Jobs (Non-Technical)

Types of problem-solving skills

Now let’s talk about four types of problem-solving skills for developers:

1.  Parallel thinking

As a software developer, parallel thinking is a crucial skill necessary to perform optimally. This makes it possible for you to carry out two tasks that complement each other at the same time (like an optimized form of multitasking skills). Being able to reorder tasks to boost parallel execution can help to improve your output and save valuable time .

2. Dissecting broad and/or complex goals

When it comes to building software, you will need to effectively outline the steps and tasks necessary to achieve your goal. Developers must learn to break large and complex tasks into smaller assignments because this is an important skill that will help you create results with precision.

3. Reimplementing existing solutions

You don’t always need to reinvent the wheel. Part of being an effective software developer comes with being able to use already existing tools before even thinking of creating new solutions. Developing problem-solving skills is very much connected to finding solutions that already exist and reusing them.

4. Abstraction

Keep in mind that goals tend to evolve. So if your client comes up with new ideas, that will mean changing your design goals and reordering your tasks. A good programmer must learn to create solutions in such a way that does not require a complete redesign from scratch.

You also have to become adept at abstracting problems so that your solutions can get them resolved so long as they aren’t entirely different from the original issue. You don’t necessarily have to abstract every aspect to avoid more complications being created. This calls for balance by abstracting only where necessary without making narrow decisions.

Read More : Learn 8 Great Benefits of Working From Home

4 Important Tips & Strategies for Improving Problem-Solving Skills

To keep your problem-solving skills and techniques from growing weaker over time, you need to exercise them non-stop. As they say: practice makes perfect!

To train the problem-solving side of your brain, these four tips and strategies can help you improve your abilities:

1. Make problem-solving a part of your life

Never restrict yourself to working on problems only during work hours. Don’t make it a chore, but, instead, do things that make problem-solving look fun. The game of chess, solving puzzles, and playing video games that compel you to think critically will help strengthen your problem-solving skills, and you can tell your significant other you are advancing your career! 🙂

When you come to a complex problem in your life, whether it’s budgeting for a home or renovating the downstairs bathroom, approach it both creatively and critically. Ask yourself: What would a great software engineer do in this situation?

2. Use different platforms to solve problems

Proffer solutions to a set of problems without restricting yourself to one platform. Using different platforms and tools regularly helps make sure you become flexible as a problem-solver. And it makes sense, because there really is no universal solution for the different problems that pop up in your line of work. Trying out different platforms to solve different problems helps you to keep an open mind and enables you to test out different techniques when looking to find solutions.

Read More : 12 Common Mistakes Keeping You From Landing Your First Developer Job

3. Be open to assistance from external sources

Part of being a good software developer comes with being able to ask for help and also accept all forms of feedback. You might need a different opinion or a new set of eyes to help find the most fitting solution to some problems. It makes sense to view building problem-solving skills as more of a team effort rather than a personal journey.

Have an open mind and heart to function not only as an individual but also as a collective. It’s a utopian working environment where everyone supports each other to become better versions of themselves. So if you come across an issue that keeps you stuck, get help! You may find someone who has a more refined framework or method you never knew existed or would have thought of using. You could then learn from them and add their solution to your toolkit.

Get feedback often, as well. This could be the catalyst to making improvements to your processes and evolving them into something truly refined.

4. Tackle new problems using lessons from past solutions

As you practice and finesse your ability to identify problems and find solutions, you’ll begin to notice patterns. It’s more like developing your toolbox armed with a wide range of solutions that have proved useful in the past. So when problems emerge, you will notice how easy it is to take some of those old solutions and apply them to the new problem.

The more you attempt to apply creativity in solving problems, the more you grow your skills. In the long run, that will help you find the right solutions faster and apply them to a wide range of problems more naturally. It’s all about improving the effectiveness and efficiency with which you tackle new problems while applying only the best possible solutions.

Read More : How to Stay Motivated at Work

3 Complementary Skills to Improve to Become a Good Problem Solver

Developing software is mostly about problem-solving at the very core before even writing your first lines of code. You have to identify problems that can be solved using software. Then you have to go on to understand how people try to solve such problems in real life.

It’s up to you to come up with a framework that allows you to take both the problem and the solution and convert them into computer code. And you have to do this in such a way that makes the software even more efficient and effective than a human.

While going through this process, developers also have to handle other problems such as deadline deliveries, checking for bugs and fixing them, and collaborate across teams. So, supporting skills must not be overlooked.

Software developers must build interpersonal skills and collaboration skills . Being able to empathize, accept feedback, handle criticism, listen intently, and show respect for others are all important characteristics and abilities necessary for teamwork, and, thus, necessary for solving problems on the job.

Read More : 5 Ways to Stand Out & Get Noticed in Your Current Development Job

Communication

No one is an island, and that’s true when you consider how software engineers work. Building software requires keeping up with clients and teammates and other departments. You can’t afford to be a Lone Ranger, at least not 100% of the time, and that’s why employers always look for good communication skills.

Being a good software developer also involves how well you can break down very complex concepts to laypeople. You want to be the kind of person who fixes a problem and is able to explain how you were able to do it. It’s all about your ability to be clear and articulate about every aspect of your work. And you want to be able to communicate not just verbally but also in written form.

To build your communication skills as a developer, you can learn from more experienced people and observe how they interact with their clients. And, don’t forget, with more and more companies becoming global enterprises and going remote, it’s important to brush up on your intercultural communication skills , as well.

Logical thinking

The difference between elite software developers and average ones is often said to be logical thinking. The ability to process thoughts logically is important, because you’ll often spend most of your time finding and fixing bugs rather than writing code.

Problems can show up from just about anywhere, even from what seems to be the most insignificant errors. So, your ability to detect software issues and solve these problems using deductive thought processes is a vital ingredient to your success as a software developer.

Read More : Questions to Ask at Interviews for Software Engineering Jobs

Problem-Solving Stages & Practices

There are countless problem-solving processes and various schools of thought regarding the best way to approach problems whenever they arise. To solve that problem, we’ve pooled some of these frameworks together to come up with a comprehensive approach to problem-solving.

Step 1 – Define the problem

You have to first start with problem identification. Knowing what you are dealing with is important, because you don’t want to risk spending valuable time applying wrong solutions. Avoid making automatic assumptions. Even when the symptoms look familiar, you want to investigate properly because such signs could be pointing to something else entirely.

Problems in software development come in different sizes and scopes. You could be having trouble getting some aspects of the product to respond in the desired way. Or maybe you’re having issues trying to decipher a codebase section where you can no longer communicate with the original developers. Sometimes, the problem could come in the form of an unfamiliar error message and you’re at loss.

Once you’re able to define the problem, make sure to document it.

Step 2 – Analyze the problem

Now it’s time to carry out problem analysis . Before deciding what problem resolution methods to adopt, it’s necessary to find out all there is to the issue, which builds on our first step. This will make it easier to come up with ideas and solutions later on.

Problem analysis isn’t always a walk in the park. There are times when the problem involves a very small mistake such as failing to import a package correctly or a small syntax error. Other times, however, it could be such a huge error, like the entire program acting differently than what you want. There might be no alarms or blinking red lights to tell you what the exact problem is.

If you encounter such situations, you can find answers by articulating the problem. Document what you intend to do, what you’ve done, the original intention for the program, and where you currently are. Communication comes in handy here, of course, not just in your documentation, but also in how you relay it to your teammates.

Read More : Got a Busy Developer Schedule? Here’s How to Keep Learning & Make Time

Step 3 – Brainstorm

This step has to do with generating ideas, and you can benefit from discussing the problem with a team and then coming up with ways to get it fixed. Keep in mind that problem-solving at work involves interacting with a diverse group of people where the individuals have unique skill sets and experiences.

Many developers tend to neglect the previous steps and rush straight into brainstorming. That’s definitely not a good way to go about problem-solving. The idea is not to skip the important steps in the process.

Once you get to the point where ideas need to be generated, do not discard any, because this step relies on a wide range of ideas. Only after gathering as many perspectives as possible should you then begin reviewing and narrowing down to the best possible solution.

Step 4 – Make a decision

At this point, all viable solutions have to be analyzed before selecting the most appropriate one to implement. Picking the best possible solution depends on its ability to meet certain criteria. It must be suitable, feasible, and then acceptable.

What it means is that the solution must be able to get the problem solved. It should also be easy to see how such a solution fits into the equation. And then every member of the team involved in the brainstorming process has to unanimously accept the solution.

Read More : How to Network as a Software Engineer

Step 5 – Implement

After identifying and choosing the solution, the next logical step is to plan out the implementation process and then execute it. Coming up with a detailed plan is crucial if the solution is to be a success.

Now this plan must detail all the necessary steps required to implement the solution. It will also explain the length of time and stages of work required. Once all of that is put in place, you can then move forward with the execution. The idea is not just to execute a solution but to do it the right way.

Implementation using automated tests can help to keep unexpected issues from arising in the future. Some other problem-solving practices or approaches begin the process with this step. So, whenever any changes are made to the project, tests asserting that the changes will perform as required will be written first before the changes are then made.

Step 6 – Evaluate

No problem-solving process can be deemed comprehensive enough if there is no room for evaluation. Whatever the solution may be, it has to undergo strict evaluation in order to see how it performs. That will also help determine whether the problem still exists and the extent to which such an issue keeps recurring.

In the event that the problem persists despite the implementation of a detailed plan, then the developer and team may even have to restart the problem-solving process. However discouraging that may sound, at least you’ll have caught it early enough. And, this also proves the process worked.

Read More : How to Become a Software Engineer: Education, Steps & Tips for Success

Final Thoughts

Developing problem-solving skills is quite necessary for software developers. To be a successful problem solver, you will need lots of years down the line to practice what you study.

Always remember that you are a problem solver first before anything else. There is more to building software than just understanding the tech behind it and writing lines of code. It’s all about improving your ability to identify problems and find solutions, and that will need lots of experience on your part.

Never shy away from problems, but learn to think critically and logically in any situation. By applying the six-step strategy for problem-solving at work discussed in this piece, you will be more equipped to come up with the most effective and efficient solutions.

We hope you enjoyed reading our guide on how to solve a problem as a software developer and ways to improve skills as a problem solver! If you have any questions, feedback, or other great problem-solving techniques or methods, let us know in the comments below 🙂

The Arc team publishes insightful articles and thought leadership pieces related to software engineering careers and remote work. From helping entry-level developers land their first junior role to assisting remote workers struggling with working from home to guiding mid-level programmers as they seek a leadership position, Arc covers it all and more!

Further reading

Here Are 43 of the Best Online Developer Communities to Join in 2024

Ready to Take On a Senior Role or Leadership Position as a Developer?

Time Management Skills for Developers: Best Tips, Tools, and Strategies

Software Engineer Degree: Pros, Cons & Alternatives

Key Analytical Skills for Developers (& How to Continually Improve Them)

Here’s When You Can TRULY Call Yourself a “Senior” Software Developer

DEV Community

Posted on Aug 10, 2022

How to develop strong problem solving skills as a software developer

Introduction.

It is generally known that problem solving is an essential skill for software engineers.

Good problem solving skills involve being able to think creatively and analytically, breaking down problems into smaller parts and using a systematic approach to find solutions. Strong problem solving skills are essential for a successful career in software development. In this article we will review some approach.

Various Methods

Trial and error method.

The trial and error method is a common problem-solving technique in which potential solutions are tried out one by one until a working solution is found. This method can be used for both simple and complex problems.

Divide and conquer

Another approach is to use a more systematic method, such as divide and conquer or reduction. Divide and conquer is a software engineering technique for solving complex problems by breaking them down into smaller, more manageable pieces. This allows for more efficient and effective problem solving by breaking down a complex problem into smaller, more manageable sub-problems. Once these sub-problems have been solved, they can be combined to solve the larger, more complex problem.

One common example of divide and conquer is the use of recursion. Recursion involves breaking a problem down into smaller sub-problems, solving each sub-problem, and then combining the solutions to the sub-problems to solve the larger problem. Another common example is the use of algorithms, such as the quick sort algorithm, which break a problem down into smaller pieces, solving each piece, and then combining the solutions to the pieces to solve the larger problem.

Once a solution is found, it is important to learn from the experience and use that knowledge to improve future problem solving skills. This includes understanding what went wrong, what could have been done better, and how similar problems can be avoided in the future. By taking these steps, software developers can become more effective problem solvers.

Problem solving skills is important in its own way. As a software developer, you should try to develop all of these skills in order to be successful.

Analytical skills:

Analytical skills are the ability to collect and analyze data, identify patterns and trends, and make decisions based on that information. They involve both logical and creative thinking, as well as the ability to pay attention to detail. Strong analytical skills are important in many different fields. Some examples:

• Being able to break down a problem and identify the various components
• Being able to identify patterns and trends
• Being able to see relationships between different pieces of data
• Being able to make decisions based on data
• Being able to solve complex problems

Creative thinking

Creative thinking in computer science is all about coming up with new and innovative ways to solve problems. It’s about thinking outside the box and coming up with creative solutions that nobody has thought of before.

It’s important to be creative in computer science because it’s a constantly evolving field. If you’re not constantly coming up with new ideas, you’re going to fall behind. Creative thinking is what keeps computer science moving forward.

If you want to be successful in computer science, you need to be creative. It’s not enough to just learn the basics. You need to be constantly thinking of new and better ways to do things. So if you’re not a naturally creative person, don’t worry. Just keep working at it and you’ll get there.

Logical reasoning

Logical reasoning is a process of making deductions based on given information. In computer science, this process is often used to solve problems and to create new algorithms. To reason logically, one must first identify the premises and then use them to reach a valid conclusion.

Practice is one of the best ways to improve your problem solving skills. You can do this by working on coding challenges, participating in online coding contests, or simply trying to solve problems you encounter in your daytoday work. Collaboration is another great way to improve your problem solving skills. When you work with others, you can learn from their experiences and share your own insights. This can help you develop a more well rounded approach to problem solving.

If you're a software developer, congratulations! You have chosen one of the most mentally demanding professions there is. And if you want to be successful, you need to have strong problem solving skills.

My last tip: get comfortable with being stuck! It's normal to feel stuck when you're trying to solve a problem and don't be afraid to ask for help. We all need help from time to time, and there's no shame in admitting that you need help.

So there you have it! Follow these tips and you'll be well on your way to developing strong problem solving skills as a software developer.

Like this article? Join the discussion in our Discord channel .

Top comments (25)

Templates let you quickly answer FAQs or store snippets for re-use.

• Work Lead Dev
• Joined Jul 12, 2022

For students , don't underestimate the mathematics. You definitively don't need a master degrees in maths to be a successfull developer BUT , mathematics train your brain to think. All this theorems you probably never used in real world , all thoses equation you resolved in high school helped your logical reasoning.

Finally, to get better at resolving problem you definitely should resolve problem :P The more you resolve , the better you get !

• Joined Mar 14, 2022

I agree with you! I mentioned it, practice and practice.. About maths it is also another alternative

• Location Yenagoa, Nigeria
• Joined Feb 1, 2021

You're right, solving mathematical problems help increase logical reasoning, and I believe that's a major reason we do maths in Computer Science. Working with numbers is a top-tier ability if you want to become a successful "software engineer". Thanks

• Joined Sep 21, 2021

Science shows that there really is no knowledge transfer between unrelated fields. There is essentially no way to get overall better at thinking. You either can relate what you know already to the thing or you can't. In first case it's experience, not brain trained to thinking, in second it depends on if you learned how to learn.

Logical reasoning is a small part that everyone does even without thinking, but it doesn't transfer if you don't use abstractions to relate what you don't know with what you do know.

You can get better at resolving problems overall, but it's a tiny improvement if you don't focus on learning how to solve problems. Solving problems on it's own gives you experience you can use at solving similar things. But it won't help with different problems.

That being said if you can relate math you learned to problems you need to solve it can sometimes make something impossible into something very easy. That on it's own is a good reason to get good at maths. The other one is training on how to read information dense domain texts.

You're right, solving mathematical problems help increase logical reasoning, and I believe that's a major reason we do maths in Computer Science. Working with numbers is a top-tier ability if you want to become a successful "software engineer". Thanks.

• Location India
• Joined Aug 17, 2019

Just like Neil deGrasse Tyson said, It is not about finding the value of x, It is about process for finding the x.

• Location Munich, Germany
• Work Software Development Team Lead
• Joined Oct 4, 2019

I have to disagree, especially on the Maths->Logics path. I found it's a lot easier to go into Logics without Maths, even though the basic principles are similar (since both are just formal languages).

• Education Computer Science
• Work Senior Software Developer at Syskron GmbH
• Joined Jan 30, 2021

What he meant is that math trains your brain. Either way it’s math or not it’s necessary to think structured to solve programming problems. I have seen so many bad code written my mathematics (no offense 😃)

• Email [email protected]
• Location Living in the path between home and office
• Education The school of life and entry points
• Work 📖 Researching and learning everything about API Security and Business Logic
• Joined Jun 22, 2022

• Location Nashville
• Education Bootcamp Grad
• Work Fullstack Developer
• Joined Mar 5, 2017

You have to joke so you don't cry.

• Email [email protected]
• Location Budapest, Hungary
• Education engineering
• Work software developer @ itemis
• Joined Dec 25, 2021

what a cool drawing!

Hahaha @apimike humor is important!

I just said that math was a way , and because it's basically taught in every school of the world (contrary to other knowledge) it's important to embrace it and understand that what you are taught is not how to multiply 2 number but actually how to think.

I realized it way too late, I always hated math when I was young because I wasn't able to figure out the point of what I was taught.

The misconception is , that you have to be good at math to be a good developer. Indeed that completely false (unless your are developing for some specific field).

• Joined Nov 24, 2020

Being a successful software developer, one needs to be open to learning and unlearning. I've learnt and unlearnt and am grateful I did. Most of the time I share with colleagues and friends, I got to find out the knowledge that was most neglected, tends to be a challenge for someone else.

It's a mentally demanding field. It's not just a job, it's a way of life.

• Location Scotland, United Kingdom
• Joined Nov 13, 2020

this is spot on

Thanks for the article, it resonates.

I read most of the comments and can't stay quiet. From my years of experience, math can be a really powerful tool when it comes to solving problems. Ofcourse is only one of the tools out there that can empower a programmer. Another tool I found to be crucial are flow charts. Being able to construct them the right way can help a lot.

e. g. This problem I solved it using only math. And I have used many concepts of math and physics for game development. To understand algebra, arrays, matrixes, vectors, magnituds, forces, inertia, acceleration, etc... Can be crucial on the development of certain softwares. But it all depends the area in which you are coding.

• Email [email protected]
• Joined Apr 23, 2019

a great read

• Location Dhaka, Bangladesh
• Education Dep. of Computer Science & Engineering(CSE), BAIUST
• Work Unemployed

A newbie here. I've a different problem . i.e. I face difficulty while implementing the code but I know the theory & logic behind it. Any suggestion/advice for me anyone ?

Hiiii maybe I will write an article about it ! Nice idea :)

• Location Rwanda
• Joined Jul 30, 2022

I think, being open-mind is a way to simulate our brain when it comes to creative thinking. btw nice article

• Joined Jul 9, 2020

I wonder if there is literature about how to improve and train your problem solving skills. Could you recommend books about this topic?

Personnaly I don't know books on this topic, but if you have got something share it with us :)

• Joined Sep 17, 2021

I have a short, simple rule: be creating and imaginary as much as possible. That's to say whatever others do you can do differently and/or more crazily.

• Email [email protected]
• Location Philippines
• Education Javascript Development with Clever Programmer
• Work Software Consultant at Servio Australia
• Joined Aug 29, 2020

Thank you. "Divide and conquer" works for me.

• Joined Mar 11, 2022

this article and that comments below are good

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The Most Important Soft Skill for Developers & How to Get Better at It

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At its core, programming is just solving problems so a computer can execute a task. Or, as one of our engineers Nick Duckwiler aptly put it: “A lot of engineering is just solving headaches.” Indeed, between fixing bugs and dreaming up app ideas that can address real world difficulties, devs need to be enthusiastic about solving problems of all sizes.   

On top of all the technical knowledge that’s required for engineering roles, you also should work on soft skills, which are personal attributes that enable you to work well with others. Problem solving is one of the most essential soft skills to have in technical positions , and luckily, there are plenty of ways to get better at tackling challenges and finding solutions.

Our course catalog just got a major update with over 70 new courses that cover professional or soft skills, like communication, leadership, productivity, and teamwork. These courses are completely free and can help you unlock essential skills for your career. In the free course Becoming a Successful Collaborator , you’ll master the meaning of collaboration, effective teaming practices, and conflict management styles, so you can enhance problem-solving, productivity, and team interconnection. Read on for more creative proven problem-solving tactics that you can try today.

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Write out the problem

Your problem won’t always come right out and say: “It’s me, hi. I’m the problem , it’s me.” In fact, something that often gets in the way of solving a problem is that we zero in on the wrong problem.

When pinpointing a problem, you can try borrowing a UX research technique that’s part of the design thinking process. After you’ve done some initial research or information gathering, you delineate your problem space and write a problem statement, which is a concise couple of sentences that succinctly define the task and offer a clear sense of direction. Write out the who, what, where, when, and why of your problem.

Getting to the core of your fundamental issue will make addressing the symptoms much easier. You can learn more about this strategy in our free course Learn Design Thinking: Ideation .

Don’t try to solve it alone

Rather than spinning your wheels trying to fix a problem on your own, consider having other people weigh in. Set up a brainstorming session for the problem you’re trying to solve, see if anyone can pair program with you, or send a Slack message to your team and see what your collective intelligence can accomplish. In the free course Expanding Your Communication Skill Set , you’ll learn how to collaborate and get things done in all kinds of workplace scenarios.

It’s easy to get tunnel vision when you’re working on a project and become fixated on one part of it. Getting more people involved in the problem-solving process will enable you to address blind spots, consider fresh perspectives, and ultimately get valuable feedback and validation for your idea. Not to mention, you’ll get experience collaborating with other people, which is a soft skill in and of itself.

Say it out loud

Ever seen a rubber duck on a programmer’s desk and wondered what it’s doing there? There’s a popular debugging technique called “ rubberducking ,” where you describe out loud what your code is supposed to do to the duck. As you verbally articulate your code and thoughts to the silent, non-judgmental duck, you may identify issues or problems that you skipped over before. Though you might have to work up the courage to talk to an inanimate object at your desk, you’ll be surprised how effective and practical rubberducking can be when it comes to pinpointing a problem.

See how other people approached the problem

Remember: You’re probably not the first person to have experienced this problem. There’s a plethora of resources that developers use to ask questions, get feedback, or crowd-source solutions for bugs. Go to Stack Overflow and see if someone else has experienced your issue and created a workaround. Or look through Docs , our open-contribution code documentation for popular languages, to see if you can find a solution. (Better yet, once you figure your issue out, you could take what you learned and contribute a Doc for folks to reference in the future.)

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Problem-Solving Mastery: Essential Skills for Developers

Despite what newcomers tend to assume, understanding the programming language, algorithms, or even a framework is never the hard part of building software! Running the best software development company is more about solving problems than simply writing codes or understanding new technologies.

Moreover, becoming an excellent problem-solver requires a lot of practice as well as experience; thus, you should be quite patient when it comes to this.

1. Practice How To Split Broad Complex Goals Into Simpler Ones

Every large and complex task can be divided into smaller and more comfortable assignments. The ability to break work into smaller tasks is often natural to humans and an essential skill to help get most things or services done.

For instance, when preparing a meal, there is a process that one follows that comprises more straightforward tasks placed in the right order, commonly known as a recipe.

However, there is a difference between a practical everyday problem such as making a meal and a more complex one like building software, and it is that the steps for building software are rarely rehearsed.

For one to be able to list the tasks necessary to come up with a particular software requires experience

2. Parallel Thinking

This is yet another crucial problem-solving skill when it comes to offering custom software development services .

Once you have already listed the steps in solving a particular problem, they can be done one at a time in the order listed, but that would not be optimal.

The art of parallel thinking helps one to be able to perform two complementing tasks at one time that can never collide.

For instance, when making a cup of coffee, you could be waiting for the water to boil as you fetch cups from your cabinet, or rather, wait for the water to boil and bring the cups after.

Reordering the tasks listed with the intention of maximizing parallel execution helps save time and also improves our overall experience.

3. Learning How To Abstract

It is important to note that the goals of a company or client who has asked you to develop software on their behalf can always change at any time, which necessitates redesigning your tasks and subgoals in the long run.

Programmers are taught how to come up with solutions so that they do not have to be designed all over again from time to time.

They also learn how to abstract issues in ways that allow for a solution to resolve any group of problems that are similar to the original one.

However, abstractions will only complicate the picture if you push them too far; thus, you should avoid over-abstracting.

If you try to abstract every aspect, you may end up with a more complicated issue than there was before. Therefore, you need to strike a balance, and you should only abstract in cases that you think will be required shortly and avoid trying to block future abstractions with some narrow decisions.

Over-abstraction is the only thing worse than under abstraction.

4. Aractice Re-Using Existing Solutions

Typically, it is not everything that has to be re-invented. Most experienced developers tend to consider using tools already available before they start designing a new solution that has never been invented.

The best software does not have to be designed from scratch. For instance, rather than making coffee, you can opt to go out and buy it from a nearby coffee shop, and thus you will have made your work much more comfortable.

Finding and re-using solutions that are already there is one of the essential problem-solving skills an experienced developer ought to have.

Also, you can always outsource solutions to your friends or other companies.

5. Learning How To Think in Terms of Data Flows

All experienced developers, after years of practice with a software development company or as freelancers, begin thinking of software as well as problem-solving in terms of data flow through a system.

Data flows through a particular series of steps that manipulate, transform, and eventually mix. When you think in terms of data flows, you can visualize the main goal and its subgoals as a series of boxes and arrows.

These boxes represent each action that affects all the materials flowing through a system, while the arrows are like pipes through which materials will flow.

Moreover, as a bonus point, a skilled developer ought to have excellent communication skills, both listening and speaking.

Typically, listening to your audience is key to solving problems and software development outsourcing in the best way possible.

Also, remember to ask questions to avoid confusion. If you get the client’s specifications wrong, then you might deliver work that your client would not be pleased with.

Also, developers are often faced with the predicament of having to explain some problematic technical info to nontechnical audiences, and thus excellent communication skills are not only essential for better client management but also for excellent internal communication.

Importance of Software Development

A business's data pool expands along with it. Effective data storage consequently becomes a top issue for the business.

Businesses must modernize and expand their digital infrastructure if they want to deliver reliable performance to all users of this data.

The creation of a software development cycle is also crucial for data analysis.

Businesses can construct a record of trends using the data from their routine tasks and share it with the appropriate software.

The creation of software is also crucial for data analysis. Businesses can construct a record of trends using the data from their routine tasks and share it with the appropriate software.

Software Development for Business Purposes

Any firm that wants to flourish must use online marketing. Online advertising will be one of the best ways to monitor the development and success of your company in the coming years.

For any business, big or small, mobile apps and online platforms are a necessity. They significantly affect how clients find you and use your goods and services.

A well-designed platform can significantly boost your revenue. These are the top 5 reasons why developing software is essential for your company.

Promote Your Company

Software development can help your company grow. Software development aids in business promotion and expansion. It makes it possible for anyone, nearly everywhere, to easily reach your brand using a computer or smartphone.

Service and Sales are Improved

It is crucial to comprehend how your target market feels about your company, brand, and items. If you want to learn what customers think of your products and services, you need an online platform that makes it simple for them to contact you and voice their ideas.

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Direct Interaction

The sole means of communication with your clientele are through software development. No other method of client interaction allows for direct contact.

This is the best technique to improve brand recognition.

More Customers are Participating

Every company seeks to increase the number of its clients. How can a business grow its clientele? Businesses must use online marketing.

A website or mobile app can help you enhance client engagement and entice them to use your products or services again.

Promoting your Company

Mobile marketing is a tool that software development enables you to use for your company. This enables you to advertise your goods and services wherever you go without having to spend more money or time.

You are accessible to customers everywhere in the world.

Marketing your Business

In business, technology is continuously evolving and expanding. To stay competitive, organizations need to be aware of these changes.

Custom business software solutions are designed to increase customer service by streamlining business operations, duties, and data management.

Higher performance, efficiency, and productivity goals are typical. This is the rationale for the creation of machines and the way that industries have changed.

Today, however, it is possible to accomplish these objectives by utilizing software solutions that are specifically developed to address corporate needs.

Every corporation is now placing a high priority on business software solutions. Software solutions can be altered to serve various needs.

Everything depends on the particular requirements of each company.

These are the top 10 reasons your business requires a specialized software solution.

Read More: What Does a Software Developer Do, How Much He or She Makes?

What is a Software Solution?

Software solutions are programs that can save time or automate tedious chores. The objective is to improve usability and efficiency.

A committed developer creates a unique software solution. It produces a software program that is specifically designed to satisfy a company's needs.

Every company, no matter how big or small, requires a unique software solution that fits their demands.

Why a Software Solution?

Custom software development refers to the creation of software that is specifically adapted to the business requirements of an organization.

Due to the significant costs associated with development, deployment, and maintenance, many organizations postpone buying custom software solutions.

These initial expenditures are minimal and are quickly recovered by solving special problems that can't be addressed by using the usual, pre-made solutions.

Because there are so many software options available, many businesses do not require a unique software solution.

Software solutions created to satisfy certain company requirements have been shown to increase productivity and efficiency.

You'll have a competitive advantage thanks to this.

The Top 10 Reasons For Creating A Specially Tailored Software Solution Are Listed Below

1. Exactly designed and developed to meet your specific business requirements

Every company is unique, and every one has specific requirements. Finding the ideal answer is so challenging. Your company may have a wide range of options and opportunities with a custom software solution, which could support your objectives for expansion and success.

You can have software tailored to your needs. It is simple to use and can be quickly spread throughout your entire company.

2. Custom Software Is a Lot More Secure

Your software is not accessible to other businesses since it is proprietary. You are therefore more secure than most people.

There will be a significant difference in the risks and dangers of external hacking and data theft if your organization has software that is specifically designed for its purposes.

An innovative software program will be used to safeguard all of your data. To meet your needs, you can add more layers.

Compared to commercial software created for many businesses, a custom software solution offers greater protection.

3. You Can Participate In Development Process

You are capable of contributing to the software development process because you are knowledgeable about your industry.

You can participate in the development process and offer suggestions and feedback to software development businesses.

4. Lower Operating Costs

Standard software is not compatible with all hardware for effective functioning. This raises the price. Custom software solutions, on the other hand, are distinct, more useful to enterprises, and cost less to implement.

Every company wants to know its ROI (return on investment). You may significantly improve your workflow and raise your return on investment by using a tailored software solution.

5. Gain an Edge Over Your Competition

A generic off-the-shelf solution's main objective is to increase the productivity and accessibility of your company.

This gives your company a competitive advantage over rivals. The software that has already been created will be extremely comparable to that of your rivals.

Your prospects of differentiating your company and achieving a progressive position in the industry are really small because you are using the same tool.

If your procedures are improved to deliver better and more efficient service, you can acquire greater dominance.

6. Automating Routine Activities

Employee fatigue may result from repeated and tedious tasks that are common in all company organizations. A specialized software solution can automate these monotonous chores.

By doing this, you'll save time and money that you can spend to expand your service portfolio, train your staff, or generate new leads.

Automating your company's tasks with a custom software solution is a terrific way to save time and money.

Read More: Software Developer vs Web Developer 8 Differences You Should Know

7. Reduce Human Errors

The likelihood of human error is substantially higher if your company is run manually. A unique software solution that can help safeguard your company from disastrous outcomes can greatly lessen these changes.

8. Integration with Third-Party Software

Your hardware and certain software are incompatible. You might seek compatibility and hardware integration if your software solution was specially created.

Software that has been customized can be easily integrated with other software. They can easily integrate with other software because of this.

9. Instant Technical Support

The ability to swiftly contact the technical support staff at your service provider or software developer is the best justification for having a bespoke solution for your business.

This enables you to immediately address any errors or glitches.

10. Custom Software License Agreement

You have total control over the creation of a unique software program for your company.

Want More Information About Our Services? Talk to Our Consultants!

You can now say with assurance that you are familiar with the most crucial skill set needed by software developers for complex problem-solving.

If you follow the advice given above, you can be sure that your career will prosper. But it's crucial to keep in mind that neither Rome nor excellence are achieved overnight.

The abilities required to excel in your career will eventually be in your possession.

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Sep 05, 2022 · 8 min read

Problem-solving skills of great developers

Developers are not strictly bound to doing plain technical work – quite interestingly opposite; development entails deep thinking and putting great focus on problem-solving tasks.

Marija Neshkoska

Content Writer

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Engaging in strategic and parallel thinking

Reusing solutions, mastering abstraction, using a variety of tools and platforms, adopting a data-flow mindset, dividing and simplifying workload, adding challenges in leisure time activities too, the takeaway.

This profession requires a lot of practice, and all experienced developers back this up. The basis, the sole start, and continuation of programming and development mean that these professionals hone their problem-solving skills daily. How developers think, speak, engage in communication (including mind-exercising activities) all sum up how they solve problems and think ahead during a task.

Practicing problem-solving doesn’t happen intentionally most of the time, and it could be said it is a type of mindset, a type of curiosity to get to the bottom of things most efficiently. Finding a solution is one thing, but enjoying the process of analyzing and overviewing is what completes the whole mental process of problem-solving in development.

With this said, we could conclude that seeking an easy way out for solutions is not enough for devs, and they need to engage mentally and sometimes even for hours on end once that deep focus starts. Working in development (and programming) includes a great passion for it foremost, and a lot of patience, as well as the ability to engage in long sessions of thinking and delving into uninterrupted focus waves. Later, this results in excelling in a specific development field as well.

In the article below, we will mention a few of the best problem-solving skills that all great software developers have in common and some comments on how all that can be achieved.

Strategic thinking is one of the best things someone could acquire, master, learn, and practice. This type of thinking, where you know how to recognize and anticipate something in advance, teaches you to calculate risks beforehand and avoid any faulty maneuvers down the road. It is a logical, rational, and calculated way of thinking through leveraging an analytical mindset.

Parallel thinking was a term well known to ancient philosophers and their approaches. It refers to thinking in more than just one direction, similar to a debate, but without any seemingly negative strategies resembling attacks and defensiveness. Instead, parallel thinking options are explored, possible solutions are thought through, facts are considered, until you finally reach a conclusion.

Strategic and parallel thinking is undoubtedly a significant asset when you need to study or practice something specific, and we can assume how valuable they are in the development industry.

In this case, a great developer can focus on one thing, for example, but still do more than one task at a given moment . When devs click and type, they already anticipate what would be needed next or what they need to focus on to resolve bugs or errors efficiently . In this way, developers think of all the possible interactions on the screen and use their ‘perspectives’ to think ahead and apply the best possible actions/solutions.

If something worked in the past, why can’t it work again? Devs have no issue using a previous efficient solution; as long as it works and does not interrupt the whole process, it can and should be reused to get a desirable result.

Problem-solving doesn’t always need to be perceived as complex , and the famous ‘Occam’s Razor’ of obvious, simple, and quick solutions can be (re)applied in many development processes.

Great devs use tools and practices that are already used and available and thus simplify their work. Where applicable (and where the task doesn’t require building something from scratch), they achieve excellent results with fewer resources.

Anyone can improve their problem-solving skills by practicing ‘abstraction.’ So, suppose parallel and strategic thinking refers to imagining possible situations, variants to existing conditions, and even possible consequences of a given action. In that case, abstracting is on the other side of the spectrum – a deep focus on the crucial thing only. Let’s elaborate.

Abstracting is crucial for developers, of course, and it’s part of building the mindset needed for this industry. But more precisely, in development, and more specifically in OOP (Object Oriented Programming), it means that the dev works exclusively with the most relevant data and ‘hides’ the rest of the data that’s not crucial at that moment in time.

Abstraction is one segment out of the three aspects of OOP, with the remaining two being ‘encapsulation’ (closely controlled access and hiding specific data) and ‘inheritance’ (transfer of data from ‘parent’ to ‘child’).

But why and how is abstraction an essential problem-solving skill? It’s simple. The dev focuses intensely on the core of the specific task without being distracted by the information they do not need at that moment . This saves time and reduces complexity overall. Perhaps this goes hand in hand with ‘work smart, not (always) hard.’

Of course, in most cases, familiarity or reusing something is practical, simple, or even needed. But, without the curiosity to propel further career advancement, sometimes developers are not motivated enough to apply this notion to practice. This is especially true in computer science and development, where writing clean code or even understanding the underlying structure of application development can make or break a product before launch.

Great devs are curious; they want to delve into deep focus, just as much as they want to explore tools and estimate how useful they’d be for their tasks . This could apply to a different programming language than the one they’ve already mastered, trying out a new technique in the development process, or even experimenting with various frameworks.

Ideally, great devs should know all the ins and outs of the industry – if one framework doesn’t work, they try another; if one programming language is not ideal for the current project, it might be the best solution for another.

Or, to find a solution to a problem with data flow in mind. This means that the excellent ‘problem-solver’ imagines the data flow and the systems in various scenarios. More precisely, envisioning how data works is not the simplest task—there are embeddings, manipulations, changes, and data transformations present in multiple steps of the app development process.

A great dev focuses on the outcome by visualizing the main goal and subgoals. Often, the mindset here includes diagram envisioning and thinking in terms of structures and sets embedded with one another or in some type of hierarchy . In summary, it involves thinking about how data moves through the system.

Devs know that “the devil is in the details”, or that focusing on smaller tasks will lead to resolving the big issue while at the same time focusing on the big picture as well.

For example, correcting bugs in the code is one way to explain this. Devs look for the bug by reviewing and looking over the entire code from start to finish—the problem may be something as tiny as a comma or a dot in the wrong place.

For a great dev to resolve a specific problem, they first need to understand the problem, and they do this by going through the entire code or each previously completed small task, for example. Division in tasks reduces the workload complexity and makes the dev focus more on possible minor issues they encounter along the way .

Last but not least, almost all great devs also engage (and excel) at mind-exercising leisure activities. Activities like chess, playing cards, and strategy board games all come in handy when thinking about the next move and what the other players/opponents might do next. It is no wonder that some great devs are outstanding gamers as well.

Everyone could benefit from adding a bit of challenge to everyday leisure activities, not just great software developers. These game-playing activities take communication skills to a whole new level by being all about focus, discipline, calculations, and logical thinking. What we learn from such activities can be a solution even to an everyday problem, not just the issues arising in the development job.

Interestingly enough, great devs already know how to think tactfully, logically, and with anticipation for what comes next, so they apply this thinking even in the choice of their leisure activities mentioned above.

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Good problem-solving skills combine various skills, experiences, mindset schemes, personality traits, and interests.

Problem-solving skills are an irreplaceable asset to have, both professionally and personally. And truth be told, all great devs have outstanding problem-solving skills. But one thing is certain, for mastering problem-solving, practice makes perfect.

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How to Improve Problem-Solving Skills as a Software Developer with SkillReactor

There’s more to software development than writing lines of code. In the first place, software developers exist to build applications that meet users’ needs. Netflix, for instance, was built to provide a steady stream of accessible entertainment to the masses. And Airbnb was created to give travelers the chance to lodge and get to know the local community better.

Put another way, true software developers are problem-solvers first and programmers second. Yet problem-solving is often the most overlooked skill among software developers . Too focused on gaining theoretical knowledge of various programming languages and frameworks, software developers today often forget to work out their problem-solving muscles.

One reason behind this is the abundance of programming videos, tutorials, books, and other learning resources available online, many of which use a spoonfeeding approach in teaching. As a result, students get lost when faced with real-world problems, unaware of where to start and how to apply the coding theories they learned. Where do they go from here?

Enter, SkillReactor .

SkillReactor helps software developers improve their coding skills and sharpens the highly underrated skill of problem-solving. How? Through its online learning platform, SkillIntern, users encounter short coding tasks that challenge them to diagnose and solve real-world industry problems.

Read on as we explore SkillReactor’s approach to training well-rounded software developers. You’ll also hear from Ryan Bell , SkillReactor’s Lead Engineer.

SkillReactor is a platform that helps deepen your understanding of programming tools and technologies, hone your coding skills, and develop core problem-solving skills vital for success in the tech industry.

How to Improve Problem-Solving Skills as a Coder with SkillReactor

SkillReactor’s approach to training is unique. It moves away from the traditional chalk-and-talk method, where teachers tell students how to code their way out of specific problems. The loophole with that approach is that students never really understand what goes on behind the code and what other methods they could take to approach a given scenario.

So, how does SkillReactor do it? SkillReactor uses the problem-based learning approach. In Ryan’s words, “This learning method helps users develop all necessary skills for software development: exposure to technologies, research and comprehension skills, and most importantly problem-solving.”

How Does SkillReactor’s Problem-Based Learning Approach Work?

As the name implies, SkillReactor’s problem-based learning approach involves presenting users with different challenges they need to solve using their coding skills. These challenges are accessible on SkillReactor’s proprietary learning platform, SkillIntern.

“The user has to analyze the requirements, research possible solutions, and then implement a working solution that fulfills the task’s acceptance criteria,” supplied Ryan.

Users get direction and pointers on the best way to approach the problem on each task, but they do not get an outright solution. Instead, they will use the clue to conduct simple research on Google or other search engines.

The platform also provides an automated validation system that lets users know if their solution is correct. If they input a wrong answer, the system provides feedback on why their response failed and what they need to do to fix it.

“This allows for an iterative approach to development that allows them to try again if they fail quickly,” explained Ryan. “The feedback from the validation allows you to act upon and improve your solution until it meets all requirements. This iterative approach further develops your problem-solving and analysis skills.”

You should also note that the tasks and projects on SkillIntern are industry-standard problems and represent a variety of unique situations you’ll likely face in the workplace. By solving these challenges, you practice your skills and gain firsthand insight into the puzzles that software developers encounter in the workplace.

Build Your Coding Skills

SkillIntern breaks these end-to-end projects into smaller tasks that you can complete with a few lines of code. Breaking large projects into smaller tasks of gradually increasing difficulty will help you better understand core back-end and front-end skills and tools and how they apply to the entire development lifecycle.

“Building a system requires you to first break down the task at hand into a series of smaller, easier to solve problems. Then, we identify the possible solutions for each problem, select the most appropriate solution, and then implement it. In essence, this means that software development is impossible without good problem-solving skills.”

What Do Software Developers Say About SkillReactor?

SkillReactor’s website features feedback from some of its users, and there seems to be no shortage of praises for the platform. Joshua Bins said, “As someone without a computer science background, this SkillReactor program was exactly what I needed to gain experience with developing a full-stack React application.”

Wajeeh Rehman also had positive things to say about his SkillReactor experience. He described SkillReactor to fit programmers of diverse experience, beginners, and experts alike. Having experienced other online courses, he spotted SkillReactor’s uniqueness.

“SkillReactor is not like a typical MOOC or learning platform in which you follow along with an instructor. Instead, you are provided with problems and a roadmap to explore and figure out how to solve them to create a functioning full-stack application. This instills problem-solving skills in beginners, which many severely lack.”

Develop Core Problem-Solving Skills with SkillReactor

SkillReactor is a platform where developers build core skills that improve their understanding of software development skills. Developers can engage in various full-stack software development projects using React, Node.js, TypeScript, and AWS Lambda programming languages.

Becoming a productive engineer also requires lots of practice and experience with independently developing solutions to many different problems. With SkillReactor, developers get that opportunity to hone their skills, gather work experience, and build projects that boost their portfolios.

Want to become a bona fide software developer and problem-solver? Register with SkillReactor today and complete a simple coding test to get started.

About us: Career Karma is a platform designed to help job seekers find, research, and connect with job training programs to advance their careers. Learn about the CK publication .

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4 steps to solving any software problem

Problem-solving is a key skill for students, new programmers, and those who work with them.

I’ve noticed a gap in technical education which oddly coincides with a skill all software developers are expected to have: the problem-solving process. I started my software career with a combination of online tutorials and a coding bootcamp, but I’ve heard similar complaints about academic computer science programs.

I’m not saying no one formally teaches these skills, but it seems more common for developers to have to figure them out on their own. Many classic (and controversial ) parts of technical interviews, like whiteboard exercises and “brainteaser” questions, are attempts to test these skills.

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That’s why, whenever I’m helping beginners learn to code, I try to walk them through the process of solving problems in the same way I would at my job. I’d like to articulate those steps here, both for software newbies who are overwhelmed by this whole “coding” thing, and to see how it compares to the process other experienced developers use.

In general, I believe the process of solving a software development problem can be divided into four steps:

• Identify the problem
• Gather information

Iterate potential solutions

Test your solution.

While I’m writing these steps with students and less experienced developers in mind, I hope everyone who works in software will find them a useful reflection on our development process. Programming instructors and anyone who mentors new programmers should make sure their students or mentees have a firm grasp of this process along with any specific technical skills they may need.

What kind of problem?

Note that when I talk about a software development problem, I mean a problem of any size and scope:

• You’re trying to do a very specific thing and you can’t get some piece of it to behave as expected.
• You’re seeing a strange error message and you have no idea what it means.
• You’re trying to figure out some cryptic section of a legacy code base when the original developers have all left the organization.
• You know generally what you want to build, but you have no idea what the individual components of the project will look like.
• You’re trying to decide what software package to use and you don’t know which one is best.
• You know there’s a function to do exactly what you want, but you can’t remember what it’s called.

Identify and understand the problem

This is easier in some cases than in others. Sometimes you get a straightforward error message and you realize you made a simple mistake: a syntax error, forgetting to pass all the variables you need into a function, neglecting to import a package.

On the other hand, sometimes the error is totally baffling. Often a bug won’t present itself with flashing red lights—the program just doesn’t do what you want it to do.

Even when this is the case, you can try your best to articulate the problem. Ask yourself the following questions (and maybe even write down the answers):

• What am I trying to do?
• What have I done already?
• What do I think the program should be doing?
• What is it actually doing?

Gathering information

Sometimes I see people skipping straight to this step without having done the previous one. Examples include:

• Googling Stack Overflow as a first step.
• Copying and pasting code—whether from Stack Overflow, a tutorial, or elsewhere in your codebase—without understanding what it does.

I believe this practice leads to “solving” problems without fully understanding them. That’s not to say any of these resources—Stack Overflow, tutorials, any other examples you find—are bad. But they should be treated as a single tool in your toolbox, not the start and end of the problem-solving process.

How else can you use this toolbox? Think about the kind of information you’re looking for:

• If you know exactly what function, class, or API endpoint you’re using from an external package or service, you can go to the relevant page in its documentation to see all the various options when using it.
• If you’re having problems with an open-source package and you don’t know why, try reading the source code for the relevant feature to make sure it’s doing exactly what you assume it is.
• To get an overview of a new tool or framework, try searching for a tutorial or quickstart guide.
• If you don’t understand why something in your code base is designed the way it is, try looking at the commit history for the relevant file or files—often you can piece together a story of what past developers were trying to do.
• And yes, search engines. Sometimes you know exactly what you want to do but you don’t know what it’s called: “PHP assign two variables.” Sometimes you want ideas on how to do something: “JavaScript shuffle a deck of cards.” And sometimes you just have no idea, but looking at other people’s similar problems can help you figure out what to try next: “Django forms validation not working.” When you do this, try to read any links or relevant documentation you find to get a broader understanding of the issue.

If I’ve been using one of these methods for a while and I don’t seem to be making progress, I’ll often switch to another. I find that a lot of developers I know reach for the search engine first, but for me, intentionally using a variety of methods helps me gain a broader scope of understanding.

Try something. It doesn’t have to be perfect. If you see anything change as a result, that’s a success. You’ll improve on it soon. Then keep trying things until you’ve made substantial progress on the problem.

If you’re in unfamiliar territory, it can help to break down the “solution” into very small increments, and try them out piece by piece. Print your data to the console before you worry about how it’ll be rendered. Call a function you haven’t used before with simple hardcoded arguments, and get it to run as expected before replacing them with the actual data you’ll be using in your application.

This still applies if you’re using someone else’s code from Stack Overflow or a tutorial as an example. Don’t just copy and paste the code into your editor—type out the code line by line. This has two advantages. First, you’re forced to engage with the code and understand it in more detail. Second, you’ll have the chance to update anything that doesn’t translate perfectly to your application. Maybe you can leave out a variable you won’t use; maybe their example uses class Animal and you’re trying to sort Books , so you’d replace a variable called species with one called title .

Sometimes it’s harder to try out what you’re doing after every line of code; that’s ok. The idea is to avoid a situation where you’re typing away at code for hours, only to find that what you created doesn’t work and you have no idea why. Try to find a middle ground, and get to results you can see within a relatively short amount of time.

If you iterate like this for a long time and don’t seem to be getting anywhere, maybe it’s time to start back at step one and try something different. But if you can get something to work, even if it’s not exactly what you had in mind, now’s a good time to move on to the next step.

Often we do this by hand: load a web page and check that it contains all the elements we expect it to render. Try replicating the conditions that led to a bug, and confirm that the bug no longer happens. Try using the feature we added in a few different ways and see what happens.

Another way we do this is with automated tests. Adding a test that asserts a feature works as predicted or a bug no longer occurs helps prevent unexpected problems down the line.

Test-driven development is an alternate approach that starts with this step rather than leaving it to the end. For each change you make to your project, you start by writing a test that asserts the change will work as predicted, then make the change.

One advantage to the test-driven approach is that it forces you to think about what success means before you start working on a given section of the project. This is a good question to ask yourself whether you start by writing a test, write one at the end, or verify your change worked by some other means. It’s part of the first step defined here—identify and understand the problem—because it’s so fundamental to finding a solution.

Even if you are writing automated tests before you add any program code, you’ll be checking that a given portion of work satisfies what you’re trying to do: running the test suite, and trying the feature to make sure it works as expected.

What’s next?

These are the steps I take to solve problems when coding, and the ones I try to impart to students and junior developers when I’m helping them with an issue. I’d like to see more coding education programs—whether in academic computer science, bootcamps, or self-paced tutorials—provide their own instructions on this process. The exact process will depend on the person, the organization, and the work they’re doing—but knowing how to solve problems is a foundational skill to being a programmer. If you work with students or less experienced developers, see what you can do to help them develop this skill.

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How to think like a programmer — lessons in problem solving

By Richard Reis

If you’re interested in programming, you may well have seen this quote before:

“Everyone in this country should learn to program a computer, because it teaches you to think.” — Steve Jobs

You probably also wondered what does it mean, exactly, to think like a programmer? And how do you do it??

Essentially, it’s all about a more effective way for problem solving .

In this post, my goal is to teach you that way.

By the end of it, you’ll know exactly what steps to take to be a better problem-solver.

Why is this important?

Problem solving is the meta-skill.

We all have problems. Big and small. How we deal with them is sometimes, well…pretty random.

Unless you have a system, this is probably how you “solve” problems (which is what I did when I started coding):

• Try a solution.
• If that doesn’t work, try another one.
• If that doesn’t work, repeat step 2 until you luck out.

Look, sometimes you luck out. But that is the worst way to solve problems! And it’s a huge, huge waste of time.

The best way involves a) having a framework and b) practicing it.

“Almost all employers prioritize problem-solving skills first. Problem-solving skills are almost unanimously the most important qualification that employers look for….more than programming languages proficiency, debugging, and system design. Demonstrating computational thinking or the ability to break down large, complex problems is just as valuable (if not more so) than the baseline technical skills required for a job.” — Hacker Rank ( 2018 Developer Skills Report )

Have a framework

To find the right framework, I followed the advice in Tim Ferriss’ book on learning, “ The 4-Hour Chef ”.

It led me to interview two really impressive people: C. Jordan Ball (ranked 1st or 2nd out of 65,000+ users on Coderbyte ), and V. Anton Spraul (author of the book “ Think Like a Programmer: An Introduction to Creative Problem Solving ”).

I asked them the same questions, and guess what? Their answers were pretty similar!

Soon, you too will know them.

Sidenote: this doesn’t mean they did everything the same way. Everyone is different. You’ll be different. But if you start with principles we all agree are good, you’ll get a lot further a lot quicker.

“The biggest mistake I see new programmers make is focusing on learning syntax instead of learning how to solve problems.” — V. Anton Spraul

So, what should you do when you encounter a new problem?

Here are the steps:

1. Understand

Know exactly what is being asked. Most hard problems are hard because you don’t understand them (hence why this is the first step).

How to know when you understand a problem? When you can explain it in plain English.

Do you remember being stuck on a problem, you start explaining it, and you instantly see holes in the logic you didn’t see before?

Most programmers know this feeling.

This is why you should write down your problem, doodle a diagram, or tell someone else about it (or thing… some people use a rubber duck ).

“If you can’t explain something in simple terms, you don’t understand it.” — Richard Feynman

Don’t dive right into solving without a plan (and somehow hope you can muddle your way through). Plan your solution!

Nothing can help you if you can’t write down the exact steps.

In programming, this means don’t start hacking straight away. Give your brain time to analyze the problem and process the information.

To get a good plan, answer this question:

“Given input X, what are the steps necessary to return output Y?”

Sidenote: Programmers have a great tool to help them with this… Comments!

Pay attention. This is the most important step of all.

Do not try to solve one big problem. You will cry.

Instead, break it into sub-problems. These sub-problems are much easier to solve.

Then, solve each sub-problem one by one. Begin with the simplest. Simplest means you know the answer (or are closer to that answer).

After that, simplest means this sub-problem being solved doesn’t depend on others being solved.

Once you solved every sub-problem, connect the dots.

Connecting all your “sub-solutions” will give you the solution to the original problem. Congratulations!

This technique is a cornerstone of problem-solving. Remember it (read this step again, if you must).

“If I could teach every beginning programmer one problem-solving skill, it would be the ‘reduce the problem technique.’ For example, suppose you’re a new programmer and you’re asked to write a program that reads ten numbers and figures out which number is the third highest. For a brand-new programmer, that can be a tough assignment, even though it only requires basic programming syntax. If you’re stuck, you should reduce the problem to something simpler. Instead of the third-highest number, what about finding the highest overall? Still too tough? What about finding the largest of just three numbers? Or the larger of two? Reduce the problem to the point where you know how to solve it and write the solution. Then expand the problem slightly and rewrite the solution to match, and keep going until you are back where you started.” — V. Anton Spraul

By now, you’re probably sitting there thinking “Hey Richard... That’s cool and all, but what if I’m stuck and can’t even solve a sub-problem??”

First off, take a deep breath. Second, that’s fair.

Don’t worry though, friend. This happens to everyone!

The difference is the best programmers/problem-solvers are more curious about bugs/errors than irritated.

In fact, here are three things to try when facing a whammy:

• Debug: Go step by step through your solution trying to find where you went wrong. Programmers call this debugging (in fact, this is all a debugger does).

“The art of debugging is figuring out what you really told your program to do rather than what you thought you told it to do.”” — Andrew Singer

• Reassess: Take a step back. Look at the problem from another perspective. Is there anything that can be abstracted to a more general approach?

“Sometimes we get so lost in the details of a problem that we overlook general principles that would solve the problem at a more general level. […] The classic example of this, of course, is the summation of a long list of consecutive integers, 1 + 2 + 3 + … + n, which a very young Gauss quickly recognized was simply n(n+1)/2, thus avoiding the effort of having to do the addition.” — C. Jordan Ball

Sidenote: Another way of reassessing is starting anew. Delete everything and begin again with fresh eyes. I’m serious. You’ll be dumbfounded at how effective this is.

• Research: Ahh, good ol’ Google. You read that right. No matter what problem you have, someone has probably solved it. Find that person/ solution. In fact, do this even if you solved the problem! (You can learn a lot from other people’s solutions).

Caveat: Don’t look for a solution to the big problem. Only look for solutions to sub-problems. Why? Because unless you struggle (even a little bit), you won’t learn anything. If you don’t learn anything, you wasted your time.

Don’t expect to be great after just one week. If you want to be a good problem-solver, solve a lot of problems!

Practice. Practice. Practice. It’ll only be a matter of time before you recognize that “this problem could easily be solved with .”

How to practice? There are options out the wazoo!

Chess puzzles, math problems, Sudoku, Go, Monopoly, video-games, cryptokitties, bla… bla… bla….

In fact, a common pattern amongst successful people is their habit of practicing “micro problem-solving.” For example, Peter Thiel plays chess, and Elon Musk plays video-games.

“Byron Reeves said ‘If you want to see what business leadership may look like in three to five years, look at what’s happening in online games.’ Fast-forward to today. Elon [Musk], Reid [Hoffman], Mark Zuckerberg and many others say that games have been foundational to their success in building their companies.” — Mary Meeker ( 2017 internet trends report )

Does this mean you should just play video-games? Not at all.

But what are video-games all about? That’s right, problem-solving!

So, what you should do is find an outlet to practice. Something that allows you to solve many micro-problems (ideally, something you enjoy).

For example, I enjoy coding challenges. Every day, I try to solve at least one challenge (usually on Coderbyte ).

Like I said, all problems share similar patterns.

That’s all folks!

Now, you know better what it means to “think like a programmer.”

You also know that problem-solving is an incredible skill to cultivate (the meta-skill).

As if that wasn’t enough, notice how you also know what to do to practice your problem-solving skills!

Phew… Pretty cool right?

Finally, I wish you encounter many problems.

You read that right. At least now you know how to solve them! (also, you’ll learn that with every solution, you improve).

“Just when you think you’ve successfully navigated one obstacle, another emerges. But that’s what keeps life interesting.[…] Life is a process of breaking through these impediments — a series of fortified lines that we must break through. Each time, you’ll learn something. Each time, you’ll develop strength, wisdom, and perspective. Each time, a little more of the competition falls away. Until all that is left is you: the best version of you.” — Ryan Holiday ( The Obstacle is the Way )

Now, go solve some problems!

And best of luck ?

Special thanks to C. Jordan Ball and V. Anton Spraul . All the good advice here came from them.

Thanks for reading! If you enjoyed it, test how many times can you hit in 5 seconds. It’s great cardio for your fingers AND will help other people see the story.

If you read this far, thank the author to show them you care. Say Thanks

Learn to code for free. freeCodeCamp's open source curriculum has helped more than 40,000 people get jobs as developers. Get started

How to Think Like a Developer: The Art of Problem Solving

• JavaScript Today
• September 25, 2023

In the fast-paced world of technology, developers are the architects of our digital age.

We are creative problem solvers who build the applications, websites, and software that shape billions of people’s lives. But what sets developers apart is not just their ability to code; it’s their unique approach to problem-solving.

To think like a developer is to embrace the art of problem-solving, a skill that goes far beyond writing lines of code.

The ability to think like a developer is a valuable skill, not only for those pursuing careers in software engineering but for anyone looking to solve complex problems efficiently. Developers are problem solvers by nature, and our approach to tackling challenges can be applied to a wide range of fields. In this article, we’ll explore the art of problem-solving through the lens of a developer and uncover strategies that can help you think like one.

The Developer’s Mindset

Thinking like a developer starts with adopting the right mindset. You need to start looking at things with curiosity and an open-mind, almost like a child.

The developer’s mindset is a unique perspective characterized by a deep-seated curiosity, a passion for problem-solving, and an unwavering commitment to continuous learning. Developers approach challenges with a tenacious drive to understand the underlying mechanisms and intricacies, much like dissecting code to uncover bugs.

We thrive on complexity, viewing problems as opportunities rather than obstacles, and are adept at breaking down daunting tasks into manageable components. This mindset values collaboration, as we often work in teams, leveraging diverse perspectives to arrive at innovative solutions.

Above all, the developer’s mindset embodies a growth-oriented philosophy, embracing mistakes as valuable learning experiences and continually seeking to push the boundaries of what’s possible in the ever-evolving world of technology.

Without further ado, let’s explore some ways in which we can improve our problem solving abilities.

1. Break Down Problems into Smaller Parts

One of the fundamental principles of problem-solving in software development is breaking down a complex problem into smaller, more manageable parts. This process, known as decomposition , allows us to focus on individual components and solve them step by step.

Whether you’re dealing with a coding issue or a real-world problem, breaking it down into smaller pieces can make it less intimidating. When faced with a problem, create a list of subproblems or tasks that need to be addressed. This structured approach can help you see the big picture while making it easier to work through each component.

Let’s take a look.

The Power of Decomposition

1. clarity and understanding.

When you’re faced with a daunting problem, it can be overwhelming. Decomposition helps you gain a clearer understanding of the problem by dividing it into smaller, digestible pieces. This clarity allows you to focus on one aspect at a time, reducing confusion and anxiety.

2. Step-by-Step Progress

Dividing a problem into smaller parts enables you to make incremental progress. As you solve each subproblem, you gain a sense of accomplishment and motivation to tackle the next one. This step-by-step approach ensures steady advancement toward the ultimate solution.

3. Improved Problem Solving

Smaller problems are often easier to solve than one large, complex issue. By addressing each subproblem individually, you can apply specific strategies, tools, or knowledge relevant to that particular aspect. This targeted approach increases your chances of finding effective solutions.

4. Collaboration

In collaborative settings, such as team projects, decomposition facilitates division of labor. Each team member can take ownership of specific subproblems, working in parallel to solve them efficiently. This streamlines the overall problem-solving process.

2. Debug Your Thinking Process

Debugging is a common term in the world of coding, but it can also be applied to problem-solving in general. Just as developers analyze code to find and fix errors, you can analyze your thought process to identify and rectify flawed reasoning or assumptions.

Debugging your thinking involves critically examining your approach and being open to adjusting it as needed.

Imagine your thought process as a complex machine with gears and circuits. Just as software developers meticulously examine their code to find and fix errors, you can apply a similar approach to your thinking.

Debugging your thinking means dissecting your mental processes to uncover and rectify flaws or biases that might be hindering your problem-solving abilities.

Start by Recognizing Assumptions : Think about the assumptions you’ve made about the problem you’re facing. These assumptions can sometimes act as hidden bugs in your thought process. Are these assumptions well-founded, or have they been made hastily?

Challenge Your Biases : Human thinking is susceptible to biases and shortcuts. Reflect on your biases, whether they’re related to your past experiences, personal preferences, or cultural influences. Are these biases influencing your perception of the problem, causing you to favor certain solutions over others?

Seek Alternative Perspectives : Just as a developer might request input from colleagues during a code review, consider seeking feedback and alternative viewpoints from others. Their insights can shed light on aspects of the problem that you might have missed or misunderstood.

Actionable Tip:

Regularly review your problem-solving process. Ask yourself if you’re making any unfounded assumptions or if there are better ways to approach the problem. Don’t be afraid to backtrack and try a different approach if necessary.

3. Use Abstraction and Generalization

Developers frequently use abstraction to simplify complex systems. This involves focusing on the most relevant details while ignoring unnecessary intricacies.

Similarly, you can apply this concept to problem-solving by identifying the core elements and principles at play. Generalization is also vital, as it allows you to apply solutions from one context to another, finding commonalities between seemingly unrelated problems.

When confronted with a problem, try to abstract the essential elements. Ask yourself if there are any similarities between the current problem and others you’ve encountered in the past. This can lead to insights and solutions.

4. Embrace Trial and Error

Developers are no strangers to trial and error. They often test different approaches, observe the results, and iterate until they find the best solution.

This willingness to experiment and learn from mistakes is a valuable mindset for problem-solving in any domain.

Again, don’t be afraid to try different strategies when facing a problem. Keep track of what works and what doesn’t, and be open to adjusting your approach based on the feedback you receive.

5. Collaborate and Seek Feedback

Collaboration is a cornerstone of software development. Developers frequently work in teams, leveraging the diverse skills and perspectives of their colleagues. Similarly, seeking input and feedback from others can be invaluable in problem-solving, as it provides fresh insights and alternative viewpoints.

When you encounter a challenging problem, reach out to others for input. Discuss your approach with peers or mentors and be open to their suggestions. Collaboration can lead to breakthroughs that you might not have achieved on your own.

6. Stay Persistent and Patient

Solving complex problems, whether in coding or other areas, often requires persistence and patience. Developers understand that some issues can be elusive and may take time to unravel. This mindset of not giving up and remaining patient can help you tackle difficult challenges with determination.

Set realistic expectations for solving problems and understand that it might take time. Keep a positive attitude, and don’t get discouraged by setbacks. Remember that persistence often leads to breakthroughs.

Thinking like a developer involves adopting a problem-solving mindset rooted in breaking down complex issues, debugging your thought process, using abstraction and generalization, embracing trial and error, collaborating, and staying persistent.

These strategies are not limited to the world of software development; they can be applied to various aspects of our life and work. By developing not only your skills, but also your problem-solving abilities with these principles in mind, you can become a more effective and efficient thinker, capable of tackling challenges with confidence. Whether you’re a developer or not, thinking like one can be a powerful asset in our technology-driven world.

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How to Build and Use Problem-solving Skills [Dev Concepts #41]

Home » News » Dev Concepts » How to Build and Use Problem-solving Skills [Dev Concepts #41]

• Author: Nikol Ruseva
• July 22, 2022
• No Comments
• algorithmicthinking , devconcept , developerskills , logicalthinking , problemsolving , programming , software engineering

To become a skilful developer means not only being familiar with a programming language or software but also having a set of skills that are fundamental to the software development process. These skills can be classified into four groups :

• Coding skills;
• Algorithmic thinking and problem solving skills;
• Fundamental software development concepts;
• Programming languages and software technologies.

Technical Skills

The skill of coding is knowledge of the basic concepts of programming. They are universal and once learned, can be applied in many programming languages. The programming language does not matter to the ability to code.

You need to know how to:

• Use development environments (the so-called IDEs) and developer tools;
• Work with variables and data, calculations, conditional statements, loops and data structures;
• Use functions, methods, classes and objects, programming APIs and libraries;
• Troubleshoot and debug code.

Now that you are familiar with the foundations of programming, you need to put that knowledge together and plan every step of finding a solution to a problem. This will require your algorithmic thinking and problem-solving skills . 

Algorithmic thinking is the ability to break a problem into a logical sequence of steps (called “algorithm”), to find a solution for every step (or break it further into sub-steps) and then assemble these steps into a working solution. 

Algorithmic thinking is similar to logical, engineering, mathematical, abstract, and problem solving. All these concepts are related to the ability to solve problems : to think logically, analyse the problems, and find and implement solutions. Problem solving is a more general skill , while algorithmic thinking is a more technical .

The fundamental computer science and software development concepts include many programming paradigms, essential software development knowledge and skills, and software engineering principles and concepts that developers typically acquire as they gain experience over time.

Some of these knowledge areas and concepts are:

• Object-oriented programming (OOP);
• Functional programming (FP);
• Asynchronous programming ;
• Relational and non-relational databases;
• The concepts behind the Web technologies.

To implement your knowledge you need to be familiar with programming languages, software development technologies, software platforms, software libraries, development frameworks and developer tools.

On the graphic below you can see an example technology stack for a Java developer.

Technologies are ever-changing and evolving , but these four groups of skills described above represent essential and stable knowledge since they will not change significantly over time. In fact, technologies are highly dependent on these skills.

Soft Skills

Soft skills are as important as the ones described above. They include the ability to communicate with people and work in a team which is essential since you as a developer will work on projects with your colleagues. You need to manage your time effectively, to be empathetic , adaptable and creative . Having attention to detail will increase your productivity at work and reduce the chances of error.

Tech Problem Solving

In the IT industry, a tech problem is often an assignment to design and implement a set of functionality which has certain input data and program state and produces output data and program state. 

Every tech problem has a goal . In programming, the goals are to design and write a working code , build an app or software system, which corresponds to the assignment and implement its requirements and functionality. Developers may encounter certain technical difficulties or limitations in designing and implementing the required functionality, like lack of resources, experience or knowledge. The process of problem solving includes finding a way to overcome these difficulties. This can be, for example, learning a new programming language, software library or framework.

Stages of Problem Solving

How to approach a tech problem? You can see in the graphic below seven stages of resolving a problem.

First of all, you need to define the problem. This involves gathering the requirements of the assignment.

After that, you analyse them. Here you should think about constraints, objects, processes and potential obstacles related to the problem. Based on a deeper understanding of the problem, you can extract the important information from the requirements and discard the non-important information, and explore its properties, which will be useful for building a solution.

The next step is to identify several solutions. You try to generate and explore different ideas and technical approaches on how to build a well-working solution. Then you analyse these ideas, their correctness, their strengths and weaknesses, their practical applicability and the costs of their implementation.   

After you have gathered some ideas you need to choose one of them. This is a decision-making process and depends mainly on the requirements, your capabilities and available resources.

After that, you need to plan and describe your actions for executing the chosen solution. You plan your algorithm. Technically, this means to write the definition of several functions, methods or classes, which will implement the chosen idea.

Sometimes planning of the algorithm is done together with its implementation, and there is no clear separation between the stages of algorithm design and algorithm implementation.

Once you have a clearly defined algorithm, you implement it . This means writing code to execute the planned steps. In software development, the implementation process includes also testing and debugging.

The last stage of problem solving is to review the results or test the solution with different input data and conditions. For software problems and apps, you need to perform testing of the code, feature by feature: to check for usual and unusual input data and conditions, check for edge cases and special cases.

Tips for Solving Problems

When it comes to solving a tech problem, the first and foremost important thing is understanding it. Take your time to read and analyse it thoroughly. Do not start to code immediately, because if you have not read the problem carefully, there is a chance of making hasty assumptions about the requirements.

Use a sheet of paper or other visualization tools . This will help you sketch your ideas fast and will improve your logical thinking. Squared paper is preferable. It works best for algorithmic problems. It helps build drawings, diagrams, tables and coordinate systems.

Write down the given input and the required output. For example, if your task is to find all odd numbers of a given array ask yourself some questions:

• What do I have?  →  An array and odd numbers.
• What is an array and how does it work? What is an odd number? What data type should I use to store it?  →  These questions will help you understand the problem .
• What is the end goal? → To filter odd numbers in the array and return it.
• How can I do it?  →  You may have multiple answers to this question and they are your potential solutions . Write them down, compare their advantages and disadvantages and then choose one of them.

After you implement the code test and debug it if needed. Make sure that you have covered all cases . Then look back and try to optimize and simplify your code making it easier to understand.

Lesson Topics

• Technical Skills;
• Soft Skills;
• Definition of a Tech Problem;
• Stages of Problem Solving;
• Tips for Solving Problems.

Lesson Slides

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How to Develop Problem-Solving Skills on Software Engineering

Gimena Aguerreberry May 20, 2021

Developing software is a rewarding endeavor because you create an efficient and easy-to-use program that solves people's problems. However, you have to be a good problem solver before getting to this end goal and launching your project.

Experienced developers will tell you that there's no way to prepare for the amount of tech issues, bugs, and human error that will come up during the development process. You have to learn how to think fast and solve problems collaboratively with others.

There are many things you can do to hone your problem-solving skills. Check out our top tips for becoming a problem solver, and you'll learn how to become a more effective software engineer quickly.

Take time to Research

Before you begin solving all your software's problems, you need to understand the problem head-on and your options available. This is where using a traditional development process can help.

In traditional problem-solving setups, the first step of problem-solving is learning more about the problem, researching it, and understanding it. Researching the topic is an essential part of this process, as you may begin to see solutions you hadn't previously recognized.

What have other developers said about this coding or framework structure bug? You can read programming books or even check out forums like r/Programming and even Quora.

Break Down Bigger Problems into Manageable Chunks

Once you better understand the problem, exercise your ability to break it down into manageable pieces. Think of it like this: an entire mountain is intimidating. But taking a step is doable. You don't need to conquer the mountain all at once. Take it one step at a time.

When we use our ability to break down a problem into simpler tasks, we not only work effectively but build our confidence and understanding of the problem. This part of the development process will improve your perspective of the problem and work like experienced developers.

Visualize Data Flows

Another method of problem-solving skills is to think in terms of data flows for your development process. Point A is the problem you start with, and you need to move it to the destination at the end: the solution.

Between the start of the process and destination, there are the arrows the data flows through, and then the boxes. Each box represents a sub-goal. If something doesn't work, you can set a new path and sub-goal.

The data will need to move through a flow chart and hit all the sub-goals to get to the destination. Each goal represents how the data will be somehow changed and manipulated.

The end of the flow is your main goal. By thinking through a data flow, you can follow the data through each transformation, easily set sub-goals, and understand how they contribute to reaching the ultimate solution!

Apply Parallel Task Management

Once you break down the problem into manageable tasks, consider when you'll need to complete each one.

One approach is to work on one task at a time. However, this can be inefficient. A more efficient approach, particularly if you're working with a team, is to work on two tasks that don't overlap.

For example, if you can do task number 3 before task 2 is finished, but you can't move onto task 4 without tasks 2 and 3 being completed, 2 and 3 can be grouped. Working on these tasks in tandem can keep you working and thinking about the problem overall.

When you don't group tasks, you may find yourself stuck on something in one task. And it can be hard to keep up your momentum. By finding tasks that complement each other, you'll learn more about your project, and working on one task could help you with the other!

Use (and Re-Use) Solutions That Already Work

Software development isn't always about reinventing the wheel. Experienced developers often take advantage of existing solutions rather than waste energy creating new solutions to old problems.

A clear example of this is with open source software development. You can save yourself time and the headache of creating hundreds of solutions and programming language algorithms that don't work like you need them to.

You can also re-use your own past successes or those of your colleagues. As you face new problems, you don't need to find novel solutions consistently. If the information is readily available, take advantage of it.

Every software engineer develops their problem-solving skills over time and improves with every project. As long as you are utilizing a process, work towards improving your skills (even if slowly doing so), and reflecting on your successes and failures, you will grow in your problem-solving skills and become an even better software engineer.

Need to develop your software with problem-solving skills that work? Our team at SOPHiLABS can take the pressure off. We have experience working through complex software engineering development issues with clients. We'll take a look at your project and work with your team to come up with efficient problem-solving solutions.

Get in touch with us today to learn more about how we can help with your software development project.

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Whether you're frustrated that the software engineers for your project won't just add features or the development process generally mystifies you, we're sure you've heard some myths about software development.

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Mobile app development isn't just about making a great product. You also need a marketing strategy that sets your product apart from the rest and even the best specialists don't get the formula right sometimes.

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Photo by Hitesh Choudhary .

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More From Forbes

12 common software development obstacles and how to tackle them.

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Developing and launching new software can be complicated. Within each step of the development and approval process, there are a lot of variables. While things can go right, there’s even more that can go wrong—and with missteps comes the possibility of having to go back to square one.

As frustrating as these obstacles are, there are ways to overcome them without severely hindering your progress. Below, Forbes Technology Council members share some of the most common issues that arise during a software development project and how teams can solve them.

1. Integration Issues

It can be challenging to integrate what you are making with tools your audience may already be using. You need to find ways to make your product compatible using application program interfaces (APIs) or partnering with these other tech brands on ways to work together. - Chalmers Brown , Due

2. Communication Breakdowns

Software development requires a team collaborating to address consumer needs. Every member has to know a project’s coding strategy, objective and goals. Otherwise, the fallout affects the manager’s reputation and the team’s output. A good manager will make sure each team member knows a project’s multiple facets and immediately educate new hires. This will increase synergy and productivity. - Arnie Gordon , Arlyn Scales

3. Unrealistic Or Mismanaged Timelines

One of the most common issues in project management is the infamous timeline. Being realistic in setting timelines with projects is critical. One of the best ways to avoid delay in timelines is to brainstorm at the beginning of the project. Ask the team, “What will break during this process?” When a bump in the timeline does occur, gather everyone and find the best way forward and around it. - Maria Mast , Management and Network Services, LLC

4. Feature Overload

The largest obstacle that I’ve observed when it comes to launching a new software package is the desire to put too much into one application. To overcome this, be more specialized rather than more general—look for sub-niches. Remember, less is more when we are trying to solve a problem. - Richard Wang , Coding Dojo

5. Lack Of Alignment Between Sponsor And User Needs

Your executive sponsor’s opinion about what should be built must be secondary to what the end user needs. Let’s face it, the chances that your boss is a Steve Jobs visionary are pretty slim, despite what they might think of themselves. Educate them on the importance of letting the market tell you what features to build. - Kishan Patel , Kunai

6. Underestimating The Task At Hand

Developers know that there can always be bumps on the road to deployment. Save yourself some time and hardship by scheduling in some extra cushion time in case it is needed. In the worst-case scenario, that space is used to conduct tests on the project or take some much-needed time off. Many times developers underestimate the task at hand, and an extra cushion can alleviate pressure and anxiety. - Alexandro Pando , Xyrupt Technologies

7. Not Pinpointing The Real ‘Why’

The most common problem is building the wrong thing. Businesses need to understand not just what a customer is asking for, but “why” they’re asking for this specifically. The driver of a horse and cart may ask for a better whip to go faster; in reality, he needs a vehicle, but he doesn’t know it. Businesses need to determine the “why” to provide the most effective software for their customers. - Bob Davis , Plutora

8. Underestimating The Importance Of Quality Assurance

To guarantee customer satisfaction, the importance of QA should never be underestimated. To obtain high-performing and secure products, code quality has to be reviewed and tested continuously throughout the development stages. Outsourcing companies can certainly alleviate this process, providing expert testers who can lead an integrated approach to maximize the quality of your project. - Nacho De Marco , BairesDev

9. Feature Creep

Feature creep—the excessive expansion of new features—is a common obstacle I’ve seen software developers confront. The most effective way to combat this issue is to consistently and thoroughly conduct customer development interviews to validate each feature and make sure it meaningfully targets the issue you set out to solve. Continue to conduct these interviews even after a successful launch. - Kison Patel , DealRoom

10. Security-Related Release Delays

Developers are often focused on getting good, working code (software) out the door. Often times, security is an afterthought that can really delay your ability to release code. It behooves developers and product managers to have security built into the development lifecycle and built into their go-to-market strategies, including any security certifications and/or other industry requirements. - James Carder , LogRhythm

11. Not Defining A Target Audience

Your new software might be cool, but not everyone will think it is. If you don’t define a target audience for your software, then you’ll waste a lot of time and money marketing it to consumers who have no interest or use for it at all. So it’s important to define your target audience before launching your new software. Do thorough audience and market research to find the best audience. - Thomas Griffin , OptinMonster

12. Underestimating The Demand

One of the unforeseen problems or obstacles to releasing new software or services is being unprepared for a highly successful launch. Often companies underestimate the volume of traffic their infrastructure may experience with the launch of a new product. Building systems that can quickly scale on demand is critical in avoiding this obstacle and ensuring your site does not crash on release. - Chris Kirby , Retired

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15 Common Problem-Solving Interview Questions

In an interview for a big tech company, I was asked if I’d ever resolved a fight — and the exact way I went about handling it. I felt blindsided, and I stammered my way through an excuse of an answer.

It’s a familiar scenario to fellow technical job seekers — and one that risks leaving a sour taste in our mouths. As candidate experience becomes an increasingly critical component of the hiring process, recruiters need to ensure the problem-solving interview questions they prepare don’t dissuade talent in the first place. 

Interview questions designed to gauge a candidate’s problem-solving skills are more often than not challenging and vague. Assessing a multifaceted skill like problem solving is tricky — a good problem solver owns the full solution and result, researches well, solves creatively and takes action proactively. 

It’s hard to establish an effective way to measure such a skill. But it’s not impossible.

We recommend taking an informed and prepared approach to testing candidates’ problem-solving skills . With that in mind, here’s a list of a few common problem-solving interview questions, the science behind them — and how you can go about administering your own problem-solving questions with the unique challenges of your organization in mind.

Key Takeaways for Effective Problem-Solving Interview Questions

• Problem solving lies at the heart of programming. 
• Testing a candidate’s problem-solving skills goes beyond the IDE. Problem-solving interview questions should test both technical skills and soft skills.
• STAR, SOAR and PREP are methods a candidate can use to answer some non-technical problem-solving interview questions.
• Generic problem-solving interview questions go a long way in gauging a candidate’s fit. But you can go one step further by customizing them according to your company’s service, product, vision, and culture. 

Technical Problem-Solving Interview Question Examples

Evaluating a candidates’ problem-solving skills while using coding challenges might seem intimidating. The secret is that coding challenges test many things at the same time — like the candidate’s knowledge of data structures and algorithms, clean code practices, and proficiency in specific programming languages, to name a few examples.

Problem solving itself might at first seem like it’s taking a back seat. But technical problem solving lies at the heart of programming, and most coding questions are designed to test a candidate’s problem-solving abilities.

Here are a few examples of technical problem-solving questions:

1. Mini-Max Sum  

This well-known challenge, which asks the interviewee to find the maximum and minimum sum among an array of given numbers, is based on a basic but important programming concept called sorting, as well as integer overflow. It tests the candidate’s observational skills, and the answer should elicit a logical, ad-hoc solution.

2. Organizing Containers of Balls  

This problem tests the candidate’s knowledge of a variety of programming concepts, like 2D arrays, sorting and iteration. Organizing colored balls in containers based on various conditions is a common question asked in competitive examinations and job interviews, because it’s an effective way to test multiple facets of a candidate’s problem-solving skills.

3. Build a Palindrome

This is a tough problem to crack, and the candidate’s knowledge of concepts like strings and dynamic programming plays a significant role in solving this challenge. This problem-solving example tests the candidate’s ability to think on their feet as well as their ability to write clean, optimized code.

4. Subarray Division

Based on a technique used for searching pairs in a sorted array ( called the “two pointers” technique ), this problem can be solved in just a few lines and judges the candidate’s ability to optimize (as well as basic mathematical skills).

5. The Grid Search 

This is a problem of moderate difficulty and tests the candidate’s knowledge of strings and searching algorithms, the latter of which is regularly tested in developer interviews across all levels.

Common Non-Technical Problem-Solving Interview Questions 

Testing a candidate’s problem-solving skills goes beyond the IDE . Everyday situations can help illustrate competency, so here are a few questions that focus on past experiences and hypothetical situations to help interviewers gauge problem-solving skills.

1. Given the problem of selecting a new tool to invest in, where and how would you begin this task? 

Key Insight : This question offers insight into the candidate’s research skills. Ideally, they would begin by identifying the problem, interviewing stakeholders, gathering insights from the team, and researching what tools exist to best solve for the team’s challenges and goals. 

2. Have you ever recognized a potential problem and addressed it before it occurred? 

Key Insight: Prevention is often better than cure. The ability to recognize a problem before it occurs takes intuition and an understanding of business needs. 

3. A teammate on a time-sensitive project confesses that he’s made a mistake, and it’s putting your team at risk of missing key deadlines. How would you respond?

Key Insight: Sometimes, all the preparation in the world still won’t stop a mishap. Thinking on your feet and managing stress are skills that this question attempts to unearth. Like any other skill, they can be cultivated through practice.

4. Tell me about a time you used a unique problem-solving approach. 

Key Insight: Creativity can manifest in many ways, including original or novel ways to tackle a problem. Methods like the 10X approach and reverse brainstorming are a couple of unique approaches to problem solving. 

5. Have you ever broken rules for the “greater good?” If yes, can you walk me through the situation?

Key Insight: “Ask for forgiveness, not for permission.” It’s unconventional, but in some situations, it may be the mindset needed to drive a solution to a problem.

6. Tell me about a weakness you overcame at work, and the approach you took. 

Key Insight: According to Compass Partnership , “self-awareness allows us to understand how and why we respond in certain situations, giving us the opportunity to take charge of these responses.” It’s easy to get overwhelmed when faced with a problem. Candidates showing high levels of self-awareness are positioned to handle it well.

7. Have you ever owned up to a mistake at work? Can you tell me about it?

Key Insight: Everybody makes mistakes. But owning up to them can be tough, especially at a workplace. Not only does it take courage, but it also requires honesty and a willingness to improve, all signs of 1) a reliable employee and 2) an effective problem solver.

8. How would you approach working with an upset customer?

Key Insight: With the rise of empathy-driven development and more companies choosing to bridge the gap between users and engineers, today’s tech teams speak directly with customers more frequently than ever before. This question brings to light the candidate’s interpersonal skills in a client-facing environment.

9. Have you ever had to solve a problem on your own, but needed to ask for additional help? How did you go about it? 

Key Insight: Knowing when you need assistance to complete a task or address a situation is an important quality to have while problem solving. This questions helps the interviewer get a sense of the candidate’s ability to navigate those waters. 

10. Let’s say you disagree with your colleague on how to move forward with a project. How would you go about resolving the disagreement?

Key Insight: Conflict resolution is an extremely handy skill for any employee to have; an ideal answer to this question might contain a brief explanation of the conflict or situation, the role played by the candidate and the steps taken by them to arrive at a positive resolution or outcome. 

Strategies for Answering Problem-Solving Questions

If you’re a job seeker, chances are you’ll encounter this style of question in your various interview experiences. While problem-solving interview questions may appear simple, they can be easy to fumble — leaving the interviewer without a clear solution or outcome. 

It’s important to approach such questions in a structured manner. Here are a few tried-and-true methods to employ in your next problem-solving interview.

1. Shine in Interviews With the STAR Method

S ituation, T ask, A ction, and R esult is a great method that can be employed to answer a problem-solving or behavioral interview question. Here’s a breakdown of these steps:

• Situation : A good way to address almost any interview question is to lay out and define the situation and circumstances. 
• Task : Define the problem or goal that needs to be addressed. Coding questions are often multifaceted, so this step is particularly important when answering technical problem-solving questions.
• Action : How did you go about solving the problem? Try to be as specific as possible, and state your plan in steps if you can.
• Result : Wrap it up by stating the outcome achieved. 

2. Rise above difficult questions using the SOAR method

A very similar approach to the STAR method, SOAR stands for S ituation, O bstacle, A ction, and R esults .

• Situation: Explain the state of affairs. It’s important to steer clear of stating any personal opinions in this step; focus on the facts.
• Obstacle: State the challenge or problem you faced.
• Action: Detail carefully how you went about overcoming this obstacle.
• Result: What was the end result? Apart from overcoming the obstacle, did you achieve anything else? What did you learn in the process? 

3. Do It the PREP Way

Traditionally used as a method to make effective presentations, the P oint, R eason, E xample, P oint method can also be used to answer problem-solving interview questions.  

• Point : State the solution in plain terms. 
• Reasons: Follow up the solution by detailing your case — and include any data or insights that support your solution. 
• Example: In addition to objective data and insights, drive your answer home by contextualizing the solution in a real-world example.
• Point : Reiterate the solution to make it come full circle.

How to Customize Problem-Solving Interview Questions 

Generic problem-solving interview questions go a long way in gauging a candidate’s skill level, but recruiters can go one step further by customizing these problem-solving questions according to their company’s service, product, vision, or culture. 

Here are some tips to do so:

• Break down the job’s responsibilities into smaller tasks. Job descriptions may contain ambiguous responsibilities like “manage team projects effectively.” To formulate an effective problem-solving question, envision what this task might look like in a real-world context and develop a question around it.  
• Tailor questions to the role at hand. Apart from making for an effective problem-solving question, it gives the candidate the impression you’re an informed technical recruiter. For example, an engineer will likely have attended many scrums. So, a good question to ask is: “Suppose you notice your scrums are turning unproductive. How would you go about addressing this?” 
• Consider the tools and technologies the candidate will use on the job. For example, if Jira is the primary project management tool, a good problem-solving interview question might be: “Can you tell me about a time you simplified a complex workflow — and the tools you used to do so?”
• If you don’t know where to start, your company’s core values can often provide direction. If one of the core values is “ownership,” for example, consider asking a question like: “Can you walk us through a project you owned from start to finish?” 
• Sometimes, developing custom content can be difficult even with all these tips considered. Our platform has a vast selection of problem-solving examples that are designed to help recruiters ask the right questions to help nail their next technical interview.

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Software engineering: problem-solving and critical-thinking.

July 18, 2023.

Software engineering isn't just about keystrokes; it's fundamentally about problem-solving and critical thinking.

Software engineering is a discipline that's all too frequently misconstrued as a task involving mere coding - the assembly of various statements in a programming language that instruct a computer what to do. However, the reality of software engineering is far more intricate, encompassing aspects of problem-solving and critical thinking. The keystrokes that form the lines of code are only the tip of the iceberg, a tangible output of a process steeped in analytical rigor, abstract reasoning, and creative problem-solving. In essence, the heart of software engineering lies not merely in the keystrokes but primarily in the process leading up to these keystrokes.

Problem-Solving in Software Engineering

The act of software engineering is fundamentally a problem-solving process . Every piece of software, be it an operating system, a mobile application, or an enterprise system, is created to address a specific problem or a set of problems. These problems could range from automating a business process to providing a platform for social interaction, to making sense of large data sets.

When engineers embark on a software development project, they start by understanding the problem they're tasked to solve. This involves comprehending the nuances of the problem, anticipating the users' needs, and outlining the constraints and requirements that bound the problem. Once the problem is understood, the next step is to conceptualize possible solutions.

This phase involves the application of several problem-solving strategies, such as decomposition (breaking the problem into smaller, more manageable parts), pattern recognition (identifying similarities between the current problem and previous ones), and abstraction (removing unnecessary details to focus on the core problem). Through these strategies, the engineer forms a comprehensive solution that can be translated into a software system.

Critical Thinking in Software Engineering

Alongside problem-solving, critical thinking forms the foundation of software engineering. Critical thinking involves the objective analysis and evaluation of an issue to form a judgment. In software engineering, it's employed at every stage of the development process.

During the design phase, critical thinking is applied when choosing between multiple potential solutions or design patterns. The engineer has to analyze each option's merits and drawbacks, considering factors such as scalability, maintainability, and performance. This requires a deep understanding of computer science principles, as well as the ability to foresee how the system might evolve in the future.

In the implementation phase, critical thinking is necessary for writing effective, efficient code. It involves selecting the right data structures and algorithms, ensuring code readability, and maintaining the software's security and integrity. Additionally, engineers need to anticipate and handle potential errors and exceptions, which require critical thinking to identify possible pitfalls and edge cases.

During testing, engineers apply critical thinking to uncover any issues that might not be apparent at first glance. This includes not just looking for evident bugs, but also identifying potential design flaws, usability issues, and performance bottlenecks.

In Conclusion

Software engineering is an intricate blend of problem-solving and critical thinking, with coding as its manifestation. The keystrokes that produce lines of code are simply a conduit, a medium through which solutions are communicated to the machine. They are the end product of a process that begins with understanding a problem, formulating a solution, and applying analytical rigor to ensure the solution's effectiveness.

As software increasingly weaves itself into the fabric of our society, the role of the software engineer expands. It's no longer enough to be a good coder; engineers must be adept problem-solvers and critical thinkers, able to navigate the complex landscape of requirements, constraints, and user needs. In the final analysis, software engineering isn't just about keystrokes; it's fundamentally about problem-solving and critical thinking.

How 7 Software Engineers Solved Their Biggest Technical Challenges

Creativity, persistence and collaboration are all essential skills for software problem-solving.

For software engineers, the pressure is on to get it right. 

After all, issues in the code can potentially affect every other facet of a product. This is especially true in the fields of education and financial technology — when people’s money or learning is at stake, it becomes even more important to approach software programming carefully and thoughtfully.

“Not being able to trade is bad,” said Wendy M, a software engineer for trading firm DRW. “But trading blindly without knowing the firms’ position can be disastrous. A bad system can bring down the entire firm.”

Roadblocks are inevitable with any project, and code is notoriously finicky. A good engineer expects these problems, and knows the true test of their mettle is how they address technical challenges when they appear. To be a true problem solver, a software engineer doesn’t need to know everything — instead, they need creativity, persistence and the ability to use the tools at their disposal. 

“In search of a solution, I resorted to the instincts carried by any child with a LEGO set: I did some serious playing and tinkering around,” said Hubert Shon, a full stack engineer at KPI Sense.

Built In Chicago spoke to software engineers at eight different tech companies and discussed the biggest challenges they’ve tackled.  Each of them showed ingenuity, resourcefulness and the understanding that their code doesn’t just affect one person or team, but the whole of the product. Read on to hear about every challenge they faced, and how each one was overcome.

What’s the biggest technical challenge you’ve faced recently in your work? What made this particular challenge so tricky?

Digital Collaboration Hub is one of Wealth Management’s digital initiatives to modernize clients’ experiences interacting with Northern Trust and to serve those who seek digitally-forward experiences. It is fun, innovative and fast-paced — but we also have to focus on security and data privacy. One of our biggest challenges is solutioning and hosting sensitive data in the cloud due to data privacy and compliance regulations. 

In order to utilize the myriad of benefits — both for the bank and our clients — that come from using the cloud, we have to demonstrate that our client’s data is secure. The kind of data — personally identifiable information (PII) — we need to store is sensitive because it could identify an individual. We must ensure that the technology solutions we build have best-in-class information security controls built in to make sure it is both preventative and detective.

How did you and your team overcome this challenge in the end? What were some of the specific tools or technologies you used?

We invited external experts to deliver workshops and training for everyone involved in the initiative — these sessions focused on information security vulnerability and the implications of using cloud-based solutions on data privacy. We also leveraged the experts from Northern Trust’s info and cyber security teams to understand current-state, applicable regulations and other factors specific to Northern Trust. Gaining an understanding of industry-leading practices, the needs of our clients and our current infrastructure allows us to put the necessary controls in place for handling data stored in the cloud. Some of the security features include encryption in transport and at rest, multi factor authentication, IP restrictions and robust access controls. We started with a proof of concept, limiting the scope of implementation and conducted rigorous testing — then we shared the design and results with various internal governance committees.

We must ensure that the technology solutions we build have best-in-class information security controls built in.”

How did this technical challenge help you grow as an engineer or help you strengthen a specific skill?

Our experience with the Digital Collaboration Hub increased our level of understanding and the organization’s comfort with cloud solutions. We learned about the constantly evolving fields of information security and data privacy, which is important for all of the work we do. At Northern Trust, we bring expertise to our clients, so we are constantly seeking to enhance our own knowledge around issues that impact them and our service. This initiative also underscored the importance of seeking external and internal expertise. This type of implementation wouldn’t work without understanding the impacts of the solution, our clients and Northern’s specific information security and data policies and perspectives. In bringing together these two pieces, we were able to think outside the box and provide cloud-based options for our most digitally-savvy clients.

Building an application is easy. Data comes in, data is processed and an output is received. Voila! How hard can it be, right? 

It’s easy when data comes in as expected, but building an application to prepare for unforeseen issues can be a bit more complex. A big part of my job is making sure that our trading platform stays up 99.99 percent of the time — however, it can be challenging to keep our system up through heavy volume days, free of network interruptions and responsive to the mandated compliance checks.

Designing a scalable distributed system that is capable of handling all of the different kinds of unexpected scenarios is particularly challenging and tricky, but it’s a part of my job that I enjoy. 

To ensure that we are prepared for any unforeseen issues to our platform, it is important that we understand all limitations — from the operation system to the overall network, from our own code to all the third-party softwares. The best approach is to avoid reaching these constraints. 

Redundancy is also one of the best resolutions to deal with unexpected failures. In the current era, anything can happen — pandemics, lockdowns, power outages or extreme weather. Sometimes unexpected scenarios are unavoidable, so being able to recover from failure and shorten the down time becomes the best mitigation to combat the unexpected. 

Lastly, collaboration and coordination are key tools in mitigating risks. Integration testing, regression testing and stress testing are important to help identify the points of failure and prevent unexpected outcomes. Before we roll out any product, we ensure that is passes thorough internal testing.

Sometimes unexpected scenarios are unavoidable, so being able to recover from failure and shorten the down time becomes the best mitigation to combat the unexpected.”

I have learned to always think of the impossible and prepare for the unexpected — not to design for what you know, but design to make ways for what you don’t know. 

When I first started working in the financial industry, I never believed that cryptocurrency would one day take off. The cryptocurrency market has evolved significantly and gained momentum in recent years which has largely impacted my role and how I think about risks. At DRW, the high standards and coding best practices create an environment for me to not just focus on designing applications for 99.99 percent availability, but to spend time developing software that can handle the 0.01 percent of defective scenarios.

The biggest technical challenge I faced recently was also one of the most interesting! What’s wonderful about Screencastify is that I always feel like my opinions are heard and I am given the space to explore, experiment and learn. Recently, we were working on a bug fix and I noticed something about some data that just seemed off. We keep a registry of all the videos users create and use the registry to enable features such as interactive questions and our watch page — there seemed to be some users that had odd patterns in their entries, as if they were creating a very high number of videos per day. Not just super users, but super duper users! 

Our initial data showed numbers that seemed somewhat benign, but because of how the incoming data was structured it was misleading. After digging a little further and aggregating more appropriately, I found a shocking number of affected entries that were resulting in unnecessary writes to our database that polluted data and would eventually have disrupted one of our newest features getting ready for wider release. This bug was lying in wait and the effects had the potential to be explosive.

Initially, the work was heavily centered around using SQL with Google’s Big Query and Firestore to search and sort the data. Ultimately, I figured out that we were seeing duplicate entries that had unique IDs and unique reference paths, and all were marked as pending uploads. At this point I pulled in a staff engineer on my team. Together, we traced the issue back to a quirk in how our system was interacting with Google Drive’s upload API: Failed uploads, on retry, were creating unique entries — and this was happening several hundred times a day on a single video. Multiply that by several thousand users and the numbers got very big, very quickly. 

Soon after these discoveries were made, the collaboration process kicked into high gear and a cross-team working group was assembled to craft a fix. This bug would have affected a major feature from another team, so it was very important we had eyes on this from them as well. Working together, we created new routes and checks to ensure it wouldn’t continue to happen. It was so great to have people in from other teams and gain insight into their features and working styles. 

Even if my hunch ended up not being correct, I would have still learned so much just engaging in the process and seeing it through.”

I think as a newer engineer it is easy to second guess yourself and assume the more experienced folks around you always know exactly what is going on — but often, the fresh eyes see things others overlook. It’s important to trust your gut, be persistent and never be afraid to ask questions. 

Most importantly, know when to ask for help and to communicate your findings with everyone — not just your team. This bug was found by me, but the ultimate impact would have been on another team’s work. Without collaboration, it may still be a lingering issue. The fix ultimately ended up being fairly straightforward, but something that I had never done with our stack. Being able to see the bug through from discovery to solution was a very rewarding learning experience and the opportunities to do this at Screencastify are plentiful. Big picture, even if my hunch ended up not being correct, I would have still learned so much just engaging in the process and seeing it through. If there’s something to learn along the way, it’s always worth doing!

Our team was tasked with creating a dynamic dashboard builder. The builder would allow users to create and edit their own charts from their chosen data, modify display properties on the fly and arrange charts into custom dashboards. 

My experience thus far as a software developer had been handling a few inputs at a time — names, dates, checkboxes, all quite manageable. Displaying multiple types of charts meant numberless possibilities of what could happen, and what could go wrong. We had also introduced a new chart library that we were still getting to know — I wasn’t sure how these new components would behave under certain conditions, or how the system would communicate. Briefly put, I was trying to build something, while still learning how it actually works. That would be concerning coming from a heart surgeon, but as my senior developer put it, “that’s pretty much all of programming!”

Online searches were the go-to resources when we didn’t have immediate answers, but the examples we found were far less dynamic and customizable than what we were trying to achieve. Little was helpful to our specific use case — we were seemingly alone in what we were trying to accomplish.

Angular projects usually revolve around predefined templates. However, the fluid nature of these dashboards pushed us to find a more flexible route: Instead of templates, we learned that these components had to be created dynamically. While examples had guided our early setup, we were finding problems. For example, we would often find a chart disappearing or seeing display settings intended for one chart get applied to all charts.

I methodically combed through the code piece by piece and line by line. All the while I asked: “How does this piece change what we are building? What possibilities does this addition now provide?”

With a deliberate process and a watchful eye on our browser’s developer tools, our breakthrough came through utilizing angular instances. While creating components dynamically, we should have also realized that we had access to the instance of that component. These instances can be stored, referenced and updated just like any other object. The discovery helped tie all the pieces of the dashboard builder together.

When building our solution, I didn’t know how to build the entire structure — but I did know how to stack up the bricks.”

If you could forgive the illustration, some of the most compelling stories of Tony Stark — the regular person behind the superhero, Ironman — are when he must face his challenges while stripped of his weaponized suit, advanced gadgetry and AI companion. Even without these powers, he still surmounts his challenges because his character is not one that relies on his privileges, but on his engineering ingenuity to piece together and build a solution. 

As an early-experience engineer, this challenge had me draw from the fundamental abilities and characteristics of a programmer. When building our solution, I didn’t know how to build the entire structure — but I did know how to stack up the bricks. I knew how these building blocks of code are supposed to behave, even if they did surprise me at times.  With this assurance and methodical approach, the application came together piece by piece. 

Technology will change and advance, but these developer qualities seem to always be a necessity. Problem solving, learning to adapt, adapting to learn and a curious itch — these are the traits that will stick with you wherever you go. And I can rely on them to keep me undaunted when the next formidable problem comes our way.

One of the biggest technical challenges we’re facing is the continuous scaling of Optiver’s machine learning (ML) capabilities in such a fast-paced environment. We have to execute extremely quickly in order to trade more effectively and efficiently in the markets, and when we’re constantly increasing the complexity of our ML models — adding more market data and signals and trading more financial instruments — it can be a challenge to keep up.

We tackled the problem in two ways. To start, we dramatically increased our machine learning pipeline’s compute and data capabilities by building a first-class compute cluster in house. This was not only to meet the immediate demand, but to also facilitate future growth. A number of different departments had to collaborate and build out new areas of expertise to meet this ambitious goal. 

At the same time, we invested in building an entirely new — and considerably more capable — framework for all of our research needs. This new fundamental building block allows us to operate more incrementally and provide more visibility and understanding of problems we encounter, while also enabling the exploration of entirely new research areas and approaches to the challenges we face.

Working on this project has exposed me to a new set of challenges, particularly involving the intersection of science and engineering.”

This project really allowed me to develop my knowledge and technical skills for building a highly-scalable machine learning platform. Prior to joining Optiver, I spent most of my career working on microkernels and low-level embedded systems, such as satellites. Working on this project has exposed me to a new set of challenges, particularly involving the intersection of science and engineering. It’s been an exciting task to overcome and I’m continuously learning along the way.

Recently we had to support the integration of varying precision fractional quantities into our existing integer quantity workflow for routing orders. This code was written in C++ using a lot of memory-efficient practices. All of our high-speed routing code was set up to only handle whole number quantities — but with the introduction of cryptocurrencies and a desire to work with more vendors, we had to pivot to handle fractional quantities as well without sacrificing performance or backward compatibility. 

Complexity mainly lay in permitting large decimal quantities of upwards of 18 digits of precision, while making sure integer quantity functionality functioned the same. JSON integers were used to represent order quantities, however much of the software was written well before the expectation of the addition of cryptocurrencies. With this in mind, we had to ensure back end code was capable of receiving both integer JSON values, as well as floating point numbers. Another issue presented with floating point numbers was the size of available data types and what we were able to store without dramatically changing our code.

Due to limitations with other pieces of our backend, we decided to forego using the JSON floating point object and instead accept both integers and string representation of numbers. The code responsible for compiling order information from JSON into serializable data basically had to implement a go-between functionality based on the type of data received. Strings are automatically parsed to determine whether there is a decimal component or not. We then split the string into two separate 32-bit integers to guarantee we have enough room to store the whole and fractional portion — allowing up to 19 digits of precision. This way, we could move forward with the original whole number routing functionality, with an optional storage for the fractional component. The value is preserved using a constant to ensure the original fractional number is returned to the backend on a response from a vendor containing the fully constructed fractional number.

Every decision should be made with purpose — and it’s important to keep in mind future improvements.”

Our C++ codebase is rather large and had been written before I started at this company a couple of years ago. As a result, to solve this particular problem I had to dig into a lot of the existing code to gain a deeper understanding of the decisions made and why they were made before willfully changing code to fit a new feature. I’d argue that this skill is the core of any decision you have to make as a software engineer. It helped me realize that every decision should be made with purpose — and it’s important to keep in mind future improvements. This makes your job easier down the line and will lead to less “hacky” design.

Another practice that our company emphasizes is test-driven development, something I wasn’t used to in the C++ realm coming from previous positions. Having tests to verify object and method behavior is invaluable when designing a new feature such as this, as it gives us a baseline to always come back to basic program functionality. Working on this challenge definitely improved my understanding and adeptness at TDD.

Our team was tasked with expanding upon the core functionality and makeup of our course content and creation. This involved a deep dive of the workings of the creation, persistence and consumption of our core course components. Extending functionality at this level is tricky due to the importance of keeping existing processes and user experiences unchanged and unaffected by the new feature set.

We took care to leverage the input of many stakeholders and experts across different areas of our platform and software stack. We created entity relationship diagrams to better illustrate ideas and uncover potential issues — these were paired with potential designs where we discussed the UI/UX process and how it related. When needed, we took a step back to reevaluate parts of the approach and altered based on newly discovered product needs.

I was able to reach out to experts in varying areas and pull ideas together to make solid, confident decisions.”

As an engineer and the lead on the main team working on these features, this process strengthened my ability to navigate through different departments. I was able to reach out to experts in varying areas and pull ideas together to make solid, confident decisions about our direction. It helped me grow in my ability to communicate ideas and issues with multiple stakeholders and balance needs and concerns.

Responses have been edited for length and clarity. Images via listed companies and Shutterstock.

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The 10 Best Problem-Solving Software to Use in 2024

Engineering Team

May 13, 2024

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Do you want a solution to help your teams work well together, reduce friction, and speed up productivity?

The best problem-solving software has all the answers for you. Problem-solving software helps find bottlenecks, simplify workflows, and automate tasks to improve efficiency. The result? Communication is easy, and your team enjoys a collaborative work environment.

Problem-solving software gives you the right visualization tools and techniques to better articulate your ideas and concepts.

That’s not all; it also automates repetitive tasks while your team focuses on brainstorming and ideating. 

In this article, we’ll cover the best problem-solving software and highlight its various features, limitations, customer ratings, and pricing details to help you make an informed decision. 

What Should You Look For In Problem-Solving Software? 

1. clickup , 2. omnex systems , 5. meistertask, 6. teamwork, 10. airtable .

Businesses encounter many challenges, from operational inefficiencies and customer complaints to financial discrepancies. 

As your team slowly navigates through these issues, having problem-solving software with the right features will reduce the hassle. Before investing in one, consider some of these following factors:

• User-friendly interface: The software should have an intuitive and easy-to-use interface to minimize the learning curve for users
• Versatility: Look for software that addresses various problem types and complexities. It should be adaptable to different industries and scenarios
• Mind maps and Visualization features: Get yourself problem-solving software solutions that offers mind maps and other visual tricks. It must be a digital canvas for your team to brainstorm ideas, connect the dots, and execute strategies
• AI assistant: If your team is stuck with repetitive mundane tasks, then it’s time you let AI take over. With the right problem-solving tool comes in-built AI that handles  everyday tasks, leaving your team to focus on the important stuff
• Automation capabilities:  Look for problem-solving process that’s all about automation. This way, you ensure efficiency and effectiveness without the grunt work
• Goal tracking: Your efforts improve when you optimize your tracking process. You need goal monitoring and tracking features to ensure you are on track 
• Cost-effectiveness: Look for the features that various plans offer and compare them to choose an option that provides maximum features while the benefits justify the cost 

The 10 Best Problem Solving Software In 2024

While you have many options, select the one with the right features that suit your needs . 

Check out our list of the ten best problem-solving tools to ensure you have the features to solve complex issues effectively: 

Henry Ford once said that success takes care of itself if everyone moves forward together. ClickUp problem-solving software helps you succeed by ensuring all your team members are always on the same page. 

With its live collaboration, you can see if your teammates are looking at or editing documents. Also, edit documents together in real-time. Moreover, any changes on any device are updated instantly, so nobody falls behind. 

The whiteboard feature is super helpful in getting your team together for brainstorming and ideating. As problem-solving involves generating and evaluating multiple ideas, the whiteboard helps write, modify, and build ideas together. 

Now that you have brainstormed on core problems, you must establish a clear visual reference point for ongoing analysis. That’s where the ClickUp mind maps feature stands out. Create a hierarchical structure, with the main problem at the center and subtopics branching out.

Since these maps have interconnections, it is easy to visualize connections between different elements. This feature effectively identifies possible cause-and-effect relationships in a problem.

ClickUp best features 

• Documentation: Address and solve problems by storing and accessing project-related documents in ClickUp Docs
• Mind maps : Identify critical connections, uncover insights, and implement creative approaches by visually mapping relationships between concepts and information with ClickUp Mind Maps
• Task prioritization: Make problem-solving easier for your software developers—sort tasks by urgency. This helps your team focus on the most crucial aspects, making problem resolution more efficient 
• Virtual whiteboards: Enhance collaborative problem-solving and critical thinking through ClickUp Whiteboards . Brainstorm, visualize ideas, and collectively work towards solutions in an interactive setting 
• Goal monitoring: Set and monitor business metrics to address challenges, track progress, and ensure the software development team remains aligned with objectives 
• Custom access rights: Customizing access rights ensures that the right individuals have the necessary permissions to contribute to problem resolution 
• ClickUp AI: Use ClickUp AI to automate repetitive tasks, analyze data for insights, and enhance productivity in tackling complex problems 

ClickUp limitations 

• Learning curve is involved in fully grasping all features and capabilities

ClickUp pricing

• Free Forever Plan 
• Unlimited Plan: $7 per month per user
• Business Plan : $12 per month per user
• Business Plus Plan : $19 per month per user
• Enterprise Plan : custom pricing 
• ClickUp AI: $5 per Workspace on all paid plans

ClickUp ratings and reviews

• G2: 4.7/5 (2,000+ reviews)
• Capterra: 4.7/5 (2,000+ reviews)

Omnex’s problem-solving software has many helpful features to track, manage, and solve problems quickly. It’s a one-stop shop for dealing with internal and external issues. 

The platform is also customer-centric, which responds to customers in their preferred formats. This ensures a tailored and user-friendly experience, further enhancing problem resolution through seamless interaction with stakeholders. 

Omnex best features 

• Define timelines and metrics for problem resolution 
• Leverage several problem-solving tools, such as 5Why, Is/Is Not, etc
• Respond to customers in various formats, including 8D, 7D, and PRR

Omnex limitations

• Initiating projects involves many steps
• Temporary delays may occur

Omnex pricing 

• Omnex has custom pricing plans 

Hive is another excellent platform to instruct your teams better while solving complex challenges and enhancing their problem-solving skills. It’s highly interactive and lets all your team members view what’s happening and express their opinions simultaneously. 

Collaborative work management helps you solve issues effectively. Hive is your virtual file cabinet where sharing documents with different teams and collaboratively working becomes more accessible. 

Hive best features

• User-friendly interface ensures seamless navigation
• Gantt view helps in mapping out project timelines
• Project hierarchies allow for easy task execution
• Kanban view allows you to understand progress better

Hive limitations 

• Being a relatively new tool, it needs frequent updates and additional features
• There are occasional bugs that slow down processes
• Locating notes from tasks and meetings is time-consuming
• Auto-generated reports are not always accurate
• Apart from ticketing, the platform needs some intuitive features

Hive pricing 

• Teams: $12 per month per user
• Enterprise: custom plans

Hive customer ratings

• G2: 4.6/5 (480+ reviews)
• Capterra: 4.5/5 (190+ reviews)

Asana is a popular problem-solving tool that speeds up decision-making . It improves project management , and its many integrations are useful. The well-organized project documents make it easy to find what you need quickly.

It’s excellent for managing many small projects and suitable for teams without complex workflows or collaboration features.

Asana best features 

• The rules and workflow feature helps automate repeating activities
• Customizable workflows help teams adapt the tool to their unique needs
• For easy understanding, organize tasks as a list, calendar, timeline, Gantt chart, or Kanban board
• Integrate with popular tools and apps such as Google Drive, Dropbox, Slack, Zoom, Microsoft, etc. 

Asana limitations

• Inefficient for handling larger projects with sub-projects and multiple workstreams
• Limited capability to measure project deviations from original plans
• Lack of comprehensive workflows and customizable animations, a feature some competitors offer
• Pricing is less favorable for smaller teams; advanced features like custom fields, portfolios, and timeline views are only available in premium plans

Asana pricing 

• Personal (free)
• Starter: $10.99 per month per user
• Advanced: $24.99 per month per user 

Asana customer ratings 

• G2: 4.3/5 (9,520+ reviews)
• Capterra: 4.5/5 (12,290+ reviews) 

Mesitertask is one of those problem-solving tools that offers strong kanban boards. These boards visualize the workflow and make it easier to identify bottlenecks and trace issues back to their source. Such visualizing features are similar to the ones found in the best root cause analysis tools . 

A customizable drag-and-drop feature further allows users to rearrange and prioritize tasks easily. Therefore, your team members will easily play around the field and segregate tasks effectively. 

Meistertask best features 

• Gain a visual representation of task timelines with a timeline view
• Streamline processes with automated workflows
• Easily categorize and prioritize tasks within sections 
• Monitor and analyze time spent on tasks for valuable insights

Meistertask limitations 

• Unnecessary negative space impacts task visibility
• Limited report and analytics features, not accessible offline
• Confusing registration process

Meistertask pricing

• Basic (free)
• Pro: $6.50 per month per user 
• Business: $12 per month per user 
• Enterprise: custom pricing 

Meister task ratings and reviews 

• G2: 4.6/5 (170+ reviews)
• Capterra: 4.7/5 (1130+ reviews) 

Teamwork is another viable problem-solving software dealing with operational challenges. It provides a clear overview of task assignments, project profitability, and other essential details. 

When combined with effective brainstorming techniques , such a clear division of work will help you solve complex issues faster. 

Teamwork features 

• Get four distinct project views, including List, Table, Boards, and Gantt
• Efficient task management simplifies the process of creating and assigning tasks to users, enhancing team collaboration  
• The time tracking feature helps determine billable hours, aiding in project budgeting and resource allocation
• Standard communication features, such as commenting and mentioning coworkers, are seamlessly integrated, promoting practical collaboration 

Teamwork limitations 

• You need to subscribe to premium plans to unlock advanced features
• The user interface is intricate and poses a challenge for some users
• Certain features, like the reminder function, do not operate on mobile apps
• Continuous email notifications have the potential to disrupt focus, as not all updates or status changes are crucial

Teamwork Pricing 

• Free Forever
• Starter: $5.99 per month per user 
• Deliver: $9.99 per month per user
• Grow: $19.99 per month per user 
• Scale: custom pricing 

Teamwork Customer Ratings 

• G2: 4.4/5 (1,070+ reviews)
• Capterra: 4.5/5 (830+ reviews)

Trello is another good option if you are searching for efficient problem-solving software. With powerful task management tools, it ensures you handle your issues efficiently. 

However, Trello’s communication and collaboration tools are not up to the mark compared to other problem-solving tools. Also, it relies heavily on integrations to do the heavy lifting.

Trello Features 

• Streamline your workflow effortlessly by arranging tasks with a simple drag-and-drop interface
• The project map feature gives a complete overview to help you visualize tasks, dependencies, and progress at a glance
• Focus on what matters the most and prioritize tasks effectively with its intuitive tools 
• Stay on top of your responsibilities with dynamic to-do lists

Trello Limitations 

• The free version imposes limitations on file attachments, a lack of advanced integrations, and automation
• Manually arranging Trello cards one by one is a time-consuming task
• There is a lack of functionality for creating a comprehensive dashboard or Gantt chart to provide a clear overview
• The absence of restrictions on card movement poses a security risk, with anyone accessing and potentially disrupting the board
• Trello becomes less practical when the board becomes densely populated with cards

Trello pricing 

• Standard: $5 per month per user 
• Premium: $10 per month per user 
• Enterprise: $17.50 per month per user 

Trello customer ratings 

• G2: 4.4/5 (13,000+ reviews)
• Capterra: 4.5/5 (23,000+ reviews)

Wrike is one of the preferred project management collaboration tools that help businesses of all sizes. With preconfigured templates for tasks, workflows, and communication, it takes the burden off your shoulders. 

It also has a user-friendly dashboard with enterprise-grade tools to manage recurring and one-time projects. 

Wrike best features 

• Planning tools to outline tasks, set deadlines, and allocate resources
• A clear visual overview helps in identifying potential challenges
• Detailed reports to analyze project performance
• Helps efficiently address issues by prioritizing tasks

Wrike limitations 

• There are no options to view projects on the Kanban board (only tasks)
• Basic project management features are missing, such as time breaks for a task
• Pricing remains on the higher end

Wrike pricing 

• Professional variant: $9.80 per month per user 
• Business variant: $24.80 per month per user 

Wrike customer ratings 

• G2: 4.2/5 (3500+ reviews) 
• Capterra: 4.3/5 (2540+ reviews) 

Monday is a cloud-based open platform, allowing businesses to collaborate better on projects. Explore many pre-built templates or create one from scratch depending on what you need. 

Monday best features

• Streamline workflows by making bulk changes efficiently
• Plan and organize tasks effectively with powerful scheduling tools
• Keep a detailed record of project activities, providing transparency and aiding in tracking progress, which is critical for troubleshooting and resolving issues
• Gain valuable insights through customizable views and comprehensive reporting, facilitating data-driven decision-making

Monday limitations 

• There is a minimum team size of three required for paid plans 
• The free trial lasts only for 14 days
• Advanced features like time tracking are only available in premium plans 

Monday pricing 

• Basic: $8 per month per user 
• Standard: $10 per month per user 
• Pro: $16 per month per user 
• Enterprise: custom pricing

Monday customer ratings

• G2: 4.7/5 (9,570+ reviews)
• Capterra: 4.6/5 (4,430+ reviews)

Airtable is a cloud-based collaboration platform that combines the simplicity of a spreadsheet with the complexity of a relational database.

It allows users to create and manage databases, spreadsheets, and other types of structured data in a flexible and user-friendly way. With its user-friendly interface,  you will quickly organize and track crucial information for problem-solving. 

Airtable best features

• Supports real-time collaboration 
• Attach files, images, and other multimedia directly to records
• Highlight and format cells based on specific conditions with conditional formatting
• Use pre-built templates for different use cases 

Airtable limitations

• While the interface is user-friendly, users unfamiliar with databases may find it initially complex
• For extremely large datasets or complex relationships, Airtable may face performance challenges
• As a cloud-based platform, it relies on an internet connection, and lack of connectivity may hinder problem-solving efforts

Airtable pricing 

• Team: $20 per month per user
• Business: $45 per month per user 

Airtable customer ratings

• G2: 4.6/5 (2,180+ reviews)
• Capterra: 4.7/5 (1920+ reviews)

Solve Problems to Drive Successful Business Outcomes

It is best to invest in problem-solving software to ensure that problems do not bog down your team and that you have the tools to solve and focus on strategic work. Our list of the ten best problem-solving software should help you find the right fit for your organization. 

Thousands of businesses of all sizes choose ClickUp. With ClickUp, you get different tools to map your project, divide tasks, view the interdependence of tasks, allocate resources, and resolve bugs on time. Whether improving team productivity or identifying and squashing bugs, ClickUp does it all!  

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Challenges of Software Developers

Before going into details of “What are the challenges faced by software developers ? “.  Let’s first know what is this Software Development ? and Who are the Software Developers ? 

Software Development :  

Software Development is the collective process of some computer science activities dedicated to the process of developing software applications. The Software Development process proceeds according to Software Development Life Cycle (SDLC) . In simple, Software Development is the process of building software applications or software products. 

Examples of Software Development – 

• Web Development
• Mobile Development
• Software Tool Development
• Application Development
• API Development
• Data Management Software Development
• Security Software Development
• Embedded Systems Development
• Cloud Computing Software Development

Software Developer :  

The Creative minds who are behind this software development or those people who are involved in the complete software development process and finally bring amazing software applications/products are the Software Developers. In simple, we can say the person who develops the computer software is called a Software Developer. 

Different types of software developers – 

• Web Developer
• Mobile App Developer
• Desktop Developer
• Graphics Developer
• Game Developer
• Big Data Developer
• Embedded Developer
• Security Developer
• Cloud Developer
• DevOps developer

After getting some ideas about Software Development and Software Developers. Now let’s move a little bit deep to analyze some common challenges faced by Software developers. 

Challenges of Software Developers :  

Here is the list of some top challenges every Software Product Developer faces – 

• Changing Requirements during the development process brings challenges for the software developers. Sometimes they won’t be able to deal with changing requirements.   
• Providing complete Security to the software applications is a major challenge for developers as hackers are trying each moment there to hack the software applications and steal the data.   
• Sometimes Misinterpreted requirements to give rise to a problem as a result the software product fails to give the actual result to the end-users.   
• Many times software developers face problems during System and Application integration leading to the failure of software projects also.   
• Further Maintenance and Upgradation become a problem for software developers for some software projects.   
• Adapting to the latest Technology becomes a big challenge for software developers when they don’t have sufficient experience with the latest market trends.   
• Sometimes when the developers don’t get the appropriate Project infrastructure for the development and deployment of projects they face problems in delivering the product.   
• Getting Defects or Errors in the product during its last stage creates an unwanted challenge for the software developers.   
• Time limitations play a vital role in software development. When there is not sufficient time for the development times the product doesn’t meet the quality standards as the developers work under pressure and output decreases.   
• When a new developer lacks proper Communication and Coordination with the other developers of the same development team it creates a problem at some point.   
• It feels like a common problem when one developer Works with another developer’s code This situation creates a problem for the developer as it takes a lot of time for the new developer to understand the code.   
• In last, most software developers face this problem if they Don’t get the required support from the Project Manager/Leader, and sometimes it gets difficult to handle the relationship between colleagues and managers which in terms decreases productivity. 

Software developers face a number of challenges in their work. Some of the most common challenges include:

• Complexity : Software systems have become increasingly complex, making it difficult for developers to understand and manage all the components of a system.
• Maintaining Quality : Ensuring the quality of software systems can be a challenging task, as developers need to account for various factors such as performance, security, and usability.
• Meeting Deadlines : Developers often work under tight deadlines, which can make it difficult to ensure the quality of the final product.
• Keeping up with new technologies: Software development is a rapidly evolving field, and developers must constantly learn new technologies and programming languages to stay current.
• Managing changing requirements: Software development projects often involve working with changing requirements, which can make it difficult for developers to plan and manage their work effectively.
• Collaboration : Collaborating with other team members, such as project managers, designers, and other developers, can be challenging as everyone have different working styles and goals.
• Debugging : Debugging software can be time-consuming and complex, particularly for large and complex systems.
• Dealing with legacy code: Developers often have to work with legacy code, which can be difficult to understand and maintain.
• Managing complexity in distributed development: Developing software in a distributed environment, where team members are located in different parts of the world, can be challenging, as it requires effective communication and coordination.
• Balancing short-term and long-term goals: While developers want to deliver the software as soon as possible, they also want to ensure that the software is maintainable and scalable in the long-term.  

HOW TO FACE THIS CHALLENGES:

Software developers can face the challenges mentioned above by implementing the following strategies:

• Complexity : Use design patterns and architecture principles to simplify the software systems and make it easy to understand and manage.
• Maintaining Quality : Use software testing and quality assurance techniques to ensure the quality of software systems, and conduct code reviews to identify and fix issues early on.
• Meeting Deadlines : Use project management techniques such as Agile development and Scrum to plan and manage work effectively.
• Keeping up with new technologies : Continuously learn and explore new technologies and programming languages to stay current.
• Managing changing requirements : Use flexible development methodologies such as Agile and Scrum to handle changing requirements effectively.
• Collaboration : Use collaboration tools such as communication platforms and version control systems to facilitate effective collaboration among team members.
• Debugging : Use debugging tools and techniques to simplify the debugging process and make it more efficient.
• Dealing with legacy code : Use refactoring techniques to improve the quality and maintainability of legacy code.
• Managing complexity in distributed development : Use communication tools and techniques to effectively coordinate and communicate with team members located in different parts of the world.
• Balancing short-term and long-term goals : Use techniques such as Test-driven development and Continuous Integration to balance short-term goals and long-term goals.

Stay Clear and Focused

No matter how big or small, solving software development challenges is by no means easy. From the challenges needed to integrating new technologies, from ensuring end-to-end security to experimental challenges – software product development requires you to be clear and focused on the problem you set out to solve in order to achieve what ‘I am determined to achieve.  

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Improve your Coding Skills with Practice

What Is Application Development?

Alan Zeichick | Content Strategist | September 6, 2024

In This Article

Application Development Explained

Why is application development important, how does application development work, benefits of application development, types of application development, appdev methodologies, app development use cases, application development best practices, artificial intelligence and app development, future of app development, cut costs and development time with oracle, application development faqs.

Back-end systems for inventory control, human resources, and accounting. Productivity applications for creating emails, documents, and spreadsheets. Customer-facing software, such as your website or mobile app. Specialized systems for IT teams, graphic designers, project managers, executives, and truck drivers.

You get the idea—it takes a lot of code to run a modern enterprise.

Most of the applications your business depends on were likely created by software vendors and are licensed, often in a software-as-a-service model. Think about your Microsoft Office, your Oracle NetSuite, or your Adobe Photoshop. Others were written or customized to your specifications, either by in-house development teams or by contractors. That second case is the focus of this article.

Application development, or AppDev, is the process of designing, creating, testing, and deploying software. Successful application development requires people with various skills. An AppDev team might have programmers, software engineers, software architects, user interface designers, testers, quality-assurance specialists, and project managers.

At its core, application development begins with a problem to solve or an opportunity to seize. Because all software takes resources to create, deploy, and maintain, there must be a good likelihood that the benefit of the user case will be equal to or greater than the cost. Once the use case is agreed on, organizations allocate resources—money, personnel, and time—for the development project, which generally follows one of two paths:

Planned development. The entire application’s requirements are mapped out in advance and approved by all stakeholders. The software is then architected, designed, tested, and deployed for use by employees or customers. This process can be achingly slow for major projects, taking years to complete—and while that’s going on, requirements change and the applications aren’t as useful as hoped.

Iterative development. A lightweight version of the software is designed, built, and tested. It’s then incrementally improved, with new features and functions added in short bursts, often taking only a few weeks. Deployments happen frequently. This approach, often called agile, is more flexible and can deliver business benefits more quickly while being responsive to changing requirements.

Key Takeaways

• Job number one for application developers is to build software that fulfills the organization’s needs.
• Many enterprise projects use agile methodologies that emphasize iterative development, user feedback, and continuous improvement to adapt to evolving business needs.
• Effective data management is essential—applications should have robust data storage, retrieval, and analysis capabilities.
• Enterprise applications need to integrate with existing systems, databases, and third-party tools.

Application development is more than simply programming. Writing code using a language such as Java , JavaScript , Python , Go , Rust , or SQL is just a fraction of the process. Teams must ensure the application will support the organization’s business use case, whether it’s increasing sales with an updated website, improving operational efficiency with an app that provides real-time insights into inventory, or boosting employee satisfaction by letting workers access paystubs and request time off through a self-service portal.

Equally important are design criteria, including the following:

• Adaptability to changing business conditions—that is, to evolutions of the use case.
• Compliance, where the application meets internal or external requirements, such as to protect the privacy of customer information or ensure that data is used and managed in accordance with a nation or region’s legal policies.
• Extensibility, so that new features can be added without requiring a lot of redesign or development.
• Interoperability to enable the new application to share data and other functionality with other applications.
• Performance, which means that the application works quickly and effectively.
• Reliability, such that the application doesn’t mangle or lose data and work won’t be lost if a system crashes.
• Scalability so that the application can take on larger workloads or serve more users without breaking or a decline in performance.
• Security, because bad actors are always trying to find and exploit vulnerabilities in code.
• Strong, intuitive user interface design (UX/UI), so that users can be successful with the software without time-consuming training.

Responsibility for all the above is mainly the responsibility of the application’s architect, and these requirements must be understood by the entire applications development team.

Without applications, most businesses would be unable to conduct day-to-day operations. For many, applications are key to competitiveness, and the ability to rapidly acquire, customize, and create new software is pivotal to their ability to adapt to rapidly changing markets.

In some cases, a business can use off-the-shelf software or tailor a commercial application by extending its functionality using APIs (application programming interfaces) or SDKs (software development kits). But sometimes, there’s no commercial application that can do what you need or handle your company’s unique expertise or intellectual property. That’s when organizations that can develop their own applications achieve a competitive advantage.

The application development process requires many steps and participants, from business stakeholders and champions to initiate and fund the project to technical specialists to create the software. Many ideas—and sometimes competing priorities—must be reconciled to deliver apps that are safe, secure, functional, and bring value to the business.

8 Stages of App Development

• Gather and analyze requirements. The complexity of gathering requirements generally aligns with the application scope. The process includes understanding the problem domain, such as the opportunity to be seized or problem to be solved. Requirements can include one or more use cases, which define what the application is going to do and who is going to use it.
• Project planning. The requirements document is used to build a project plan, which will include a budget, a timeline, the methodology to be used, and a list of resources, such as the skills needed for the development team. It also details the software development platforms and tools needed and where the application will be deployed.
• Design and architecture. This is where big questions, such as the modular flow of the application, are answered. The design takes into account all the above considerations as well as the technical factors needed to provide security, compliance, reliability, scalability, and usability.
• Coding and development. Now programmers begin actually writing the software using the chosen methodology, programming languages, and tools. Depending on the methodology used, coding/development and testing may be done as separate stages or in parallel.
• Testing. Every bit of code must be tested to ensure that it functions correctly, meets security requirements, and hits performance goals. Some testing is done on a line-by-line basis on the code; other testing, called user acceptance testing, is performed by business users who validate that the application does what they want and helps meet the use case.
• Deployment. Once the application is complete—or complete enough to be useful—and passes all the necessary tests it is “thrown over the wall” from a development environment to a production environment, so that it can be used by customers, employees, and partners. Based on feedback, plans will be made for the next iteration of the application, which adds more functionality.
• Maintenance. Most software degrades over time, as bugs and security issues are discovered, platforms change, and increasing use slows performance. The development team or a maintenance group addresses those issues and also handles such concerns as data backups or performance tuning. Maintenance also looks for ways to lower the operating costs of the application, which may include migrating it to the cloud or replacing it with newer, less expensive software or services.
• Decommissioning. At some point, the application may no longer be needed or fit for purpose. Perhaps the requirement goes away, or the functionality is rolled into another application, or the use cases are reimagined and an entirely new application is created. Rarely can you simply turn off or erase an unwanted application, however. Instead, the data, user accounts, and features need to be carefully migrated to the new system, and then the old application archived in case it needs to be examined in the future.

Why create software? There are two main reasons: It’s your business, or it helps your business.

• Applications might be what your company offers to customers as your product or service. Think of Oracle, for example, or of your favorite computer game developer or a consultancy that writes software for its clients.
• If you’re not in the software business, you may need specialized applications to run your organization. That’s the type of application development we’re mainly covering here, although the information in this document is also applicable to businesses selling or licensing software to others.
• Buying or licensing existing applications is fast, and when possible, is an excellent choice. When the right applications don’t already exist, that’s when companies choose to design and write their own software, using either internal staff or contractors. Having their own bespoke applications lets a company seize opportunities, reinforce its brand, solve problems, and react quickly to changing market conditions. Having custom applications for use by employees and customers—whether running natively on a laptop or desktop, through a browser, or in a mobile app—also can provide a competitive edge. The custom application is an investment: This software is an owned asset and can be a significant part of its intellectual property.

Not all applications are built the same way. Huge software development projects involve a formal process that might take months or years to deliver a usable application. Smaller projects might be knocked out in a week—or in a day. The project’s stakeholders will work with the technical development team to determine the best approach.

Low-code/no-code

Not all applications require the full-on efforts described above. Think back a few decades, where power users—sometimes called “citizen developers”—created sophisticated spreadsheet macros to solve business problems. More recently, a type of development called low-code/no-code has emerged to allow business users to write applications using visual tools that allow them to use specific data sources, algorithms, and workflows. These applications run in the cloud and can be accessed by employees, customers, or other partners. Often, those no-code/low-code apps run in a standard web browser or on a mobile device, such as a phone, tablet, or kiosk.

There are many benefits of the low-code/no-code approach, including much faster development and deployment; the built-in security model of the hosting platform; considerably lower cost to build and maintain; and, of course, reducing the need for professional software developers while empowering employees. However, professional developers also like these tools to handle simpler problems that don’t require a full-on application development project.

While low-cost/no-code applications can’t rival the sophistication of an application built from the ground up by architects, designers, coders, and testers, they can outperform spreadsheet customizations and offer a sophisticated, easy-to-use interface appreciated by nonprogrammers. These apps can also be used to tie other applications together on an ad-hoc basis—perfect for handling short-term problems or seizing immediate opportunities.

The streamlined nature of these tools is also practical for experienced programmers. Check out Oracle APEX to get started with low-code application development.

Mobile application development involves a wide range of tools, services, and products for creating and distributing apps. Google Android and Apple iOS are the most popular platforms for mobile apps, and they support a range of development tools and methodologies. Mobile applications are often designed using a microservices architecture, where the application is broken up into smaller tasks that communicate with one another.

Because of the ubiquity of Android and iOS devices and the always-connected nature of phones and tablets, many businesses have embraced mobile apps as a great way to serve both employees and customers. In the corporate world, employees use mobile apps for sales, enterprise resource planning, employee HR self-service, security, timecards, messaging, and more. While many mobile apps are created by specialist companies, you can also design, develop, and deploy them in-house for your employees and customers.

Enterprise applications run on data like sales transactions, product price sheets, HR materials, emails, banking records, customer contact information, and company financials. The most efficient place to store enterprise data is in a database, so it can be readily retrieved, searched, updated, protected, and analyzed.

Both off-the-shelf and custom applications can access databases through highly efficient query languages, standard data exchange formats, and robust programming interfaces. However, some high-end databases, such as Oracle Database 23ai , can actually run applications within the database engine itself, which often provides applications with fast, secure, and robust access to that data. Development tools can target the database engine itself for such applications, an approach that has the added benefit of enabling database administrators to manage and tune those apps after they are deployed.

Microservices

Applications designed in a cloud microservices architecture tend to be easy to maintain and deploy and very robust. There might be hundreds or thousands of tiny microservices, each a building block written to efficiently perform a single task and to communicate with other applications or microservices using simple communications protocols.

Microservices-based applications are highly scalable, too; the cloud-centric design and architecture mean that if a particular service is heavily used, the cloud can simply make and run lots of copies as required—automatically. In addition, because individual microservices are focused on a specific task, they are easy to design, code, test, and deploy.

The development team’s approach to building an application is the methodology. The term includes design philosophies; project management approaches; and interactions between the development team, customers, and other key stakeholders. Sometimes the methodology dictates, or at least informs, the decision on technical tools that will be used by the development team.

No matter which methodology is chosen, there are two truths: The goal is always a successful project, and everyone involved will have an opinion. Broadly speaking, modern software development methodologies fall into two basic categories: waterfall and agile.

Waterfall development, also known as the monolithic or classical model, focuses on a linear progression of steps: Gather requirements, design, code, test, approve, deploy, maintain. Each step is performed thoroughly, and you proceed to the next step only once the previous one is complete. Once a step has been completed, it is rarely, if ever, revisited, which means that waterfall development can’t adapt to rapidly changing situations or evolving enterprise needs. That makes waterfall approaches best for projects that must be right the first time—such as the software that goes into a car, nuclear power plant, or medical device.

Agile development takes the opposite approach. Agile focuses on the rapid implementation and deployment of applications by building a small, minimally viable product (MVP), and then making iterative improvements to add new features and functions, address shortfalls, leverage new technologies and ideas, and improve performance.

There is no one agile methodology ; in fact, there are dozens, each with its own history, adherents, and rationale. In the case of test-driven development, for example, before coders create a new piece of code, they first write the automated tests that will ensure that the new code works correctly. This helps ensure that all the code is tested before being incorporated into the latest iteration of the application.

Most agile methodologies require that each iteration is very short, often just a couple of weeks in duration. During those iterations, called sprints, the development team focuses on adding features or functionality to the application.

Sometimes an application is conceptually easy to design and deploy, such as a forms-based app, a report writer, or a query tool for a database. In those cases, a full-blown application development process like waterfall or agile may be unnecessary. That’s where rapid application development, or RAD, comes in. RAD falls into the agile bucket and is characterized by easy-to-use tools that let a very small development team—or even a single person—create a user interface, code the internal logic, and link into enterprise data sources.

Historically, RAD development was used to create a visual mock-up of a desired application so that developers and stakeholders could agree on appearance and functionality before the “real” programming effort began. That led to another term for RAD, rapid prototyping. However, with the advent of low-code and no-code tools, RAD development has proven useful for simple applications that could be built and deployed based simply on that rapid prototype. What’s more, development time may be slashed to days, which delights business users. If an application can be built with a RAD approach, it often should be.

Key Differences

Here are three examples of different enterprise applications built with specific methodologies to best suit the use cases.

• A healthcare company uses low-code/no-code development to manage clinical trials. The company uses a low-code tool, running in the cloud, to cost-effectively develop its own user interface. By developing its own platform, the company can better monitor its deliveries, thus improving customer service. The application can scale to thousands of users and projects for key clinical study monitoring information. After adopting a low-code approach, the company saved significant costs over the course of five years through more efficient operations and reduced application management effort.
• A logistics company builds mobile apps that integrate with Oracle cloud-based supply chain applications. Previously, applications ran on a desktop PC in a browser, but as the company deployed more mobile and handheld devices, it needed more flexibility. With the mobile app, warehouses and product distributors can scan and process inventory on the spot against their supply chain management system, improving the accuracy of data and speeding the ability to act on that data quickly.
• An employment services firm runs its job training, up-skilling, and talent development services platform using a microservices architecture running in Oracle Cloud Infrastructure. Today, hundreds of thousands of people use these platforms daily, enabling them to find, apply, and prepare for gainful employment. The platform supports 5,000 simultaneous users and processes up to 10,000 requests per minute; whenever a new version of the application is ready, managed cloud services automate updates quickly and with zero downtime.

Applications can empower customers and employees, expand the business, or simply address pain points. That being said, application development can also be expensive and resource-intensive—and if the new software has security flaws, can represent a risk for the company and its customers. Here are some best practices that can help minimize risk and maximize success.

• Scope the job properly. Successful development projects solve a business problem or realize an opportunity. Creating an application is an expensive undertaking, so it’s worth spending time on a comprehensive requirements document.
• Move fast but keep the end goal in mind. The sooner the application can be used, the sooner the business can realize the benefits. An iterative, agile approach to development emphasizes flexibility and continuous improvement. It involves developing features in short sprints and gathering user feedback regularly. This allows for faster course correction and ensures the final product aligns with user needs.
• Prioritize code quality, security, and standards. Development teams must emphasize security as well as scalability and performance and ensure software is readily usable by the target audience. Strive for a clean, intuitive interface that efficiently guides users through tasks and minimizes frustration.
• Keep the journey going. Application development processes need to be able to react to changing business needs. Ensure the development team or a maintenance group addresses any issues that arise with an application and are responsive to such concerns as new data sources or performance tuning.

Generative AI is being used for many text-oriented tasks: Summarizing reports, writing sonnets, drafting customer service emails, making chats more contextual. Turns out that GenAI is good at writing software code, too: A programming language is a language, and from a software perspective, it’s not very different from English, Spanish, or Mandarin.

When it comes to application development, GenAI is good at translating a developer’s written intent, expressed in a conversational human language, into completed, ready-to-run code. Based on early experiments, this AI-generated code is functional, efficient, and secure. This is most apparent in parts of the code that are tedious to develop, such as database access code or the boilerplate text that is used to set up microservices.

Another area where GenAI can help developers is in examining human-written code to look for errors, spot potential vulnerabilities, and point out where the programmer didn’t follow best practices. Expect AI-based assistance to become a standard feature of mainstream software development tools and platforms.

Software development is an evolving practice. As noted, GenAI will be a huge help by freeing developers from tedious tasks. It will become a staple for application development and will be embedded into mainstream development tools. New architectures such as microservices will allow new applications to be built quickly by leveraging a modular approach. But there are other trends that we have noted.

Security stays top of mind. Bad actors will continue to threaten organizations, so applications must not only be designed and built for security, but they also need to be continually updated as new attack tools come online.

Mobility is here to stay. For many people, a smartphone is their primary computing device, which means that organizations must be comfortable building mobile apps or designing for use on a mobile browser.

Dev democratization. Employees will continue to demand no-code/low-code tools that allow them to develop their own applications quickly. How will you encourage this without sacrificing quality or security?

Oracle offers a wide array of development tools, services, and platforms that can accommodate any application development project. In addition, Oracle delivers the industry’s most complete collection of ready-to-use business applications that can be customized and integrated with your own applications to help address your needs.

Where to deploy? Oracle offers the second-generation Oracle Cloud Infrastructure (OCI) , which has the databases, developer services, integration services, and storage you’ll need. Those are augmented by networking, analytics and business intelligence, low-code/no-code tools, and new AI services that can be leveraged by business applications. Add to that Oracle’s application security, compliance, and cost-management tools, and you’re ready to go.

Compared with other clouds, Oracle offers better price/performance, lower storage costs, and 48 commercial and government regions around the world to better meet your needs. Not looking for the cloud for your next project? Check out Oracle’s on-premises systems, including the Oracle Exadata enterprise database platform.

You can examine the tremendous range of Oracle’s developer technologies , and then see how you can build, test, and deploy applications on Oracle Cloud—for free .

AppDev democratization via the next generation of low- and no-code development tools is just one of our 10 trends CIOs must track this year. See what other ops the cloud offers to move your business forward.

What does an application developer do?

An application developer builds business applications—or more accurately, is a member of a team building those applications. A developer needs to have technical skills, such as knowledge of agile methodologies; one or more programming languages such as Java, SQL, Python, and JavaScript; and a solid understanding of software architectures. Specific responsibilities can include architectural design, coding, testing and debugging, user interface design, database integration, report writing, and software maintenance.

What are the steps in application development?

There are eight main steps in application development; some of these may be done in parallel, and depending on the methodology, may be performed iteratively.

• Gather and analyze requirements
• Project planning
• Design and architecture
• Coding and development
• Maintenance
• Decommissioning