problem solving as a software engineer

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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

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.

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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
• Pronouns He/Him
• 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.

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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 provides articles and expert advice on tech careers and remote work. From helping beginners land their first junior role to supporting remote workers facing challenges at home or guiding mid-level professionals toward leadership, Arc covers it all!

Further reading

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

Here Are 43 of the Best Online Developer Communities to Join in 2025

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

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

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

Software Engineer Degree: Pros, Cons & Alternatives

What Is Problem Solving? How Software Engineers Approach Complex Challenges

From debugging an existing system to designing an entirely new software application, a day in the life of a software engineer is filled with various challenges and complexities. The one skill that glues these disparate tasks together and makes them manageable? Problem solving . 

Throughout this blog post, we’ll explore why problem-solving skills are so critical for software engineers, delve into the techniques they use to address complex challenges, and discuss how hiring managers can identify these skills during the hiring process. 

What Is Problem Solving?

But what exactly is problem solving in the context of software engineering? How does it work, and why is it so important?

Problem solving, in the simplest terms, is the process of identifying a problem, analyzing it, and finding the most effective solution to overcome it. For software engineers, this process is deeply embedded in their daily workflow. It could be something as simple as figuring out why a piece of code isn’t working as expected, or something as complex as designing the architecture for a new software system. 

In a world where technology is evolving at a blistering pace, the complexity and volume of problems that software engineers face are also growing. As such, the ability to tackle these issues head-on and find innovative solutions is not only a handy skill — it’s a necessity. 

The Importance of Problem-Solving Skills for Software Engineers

Problem-solving isn’t just another ability that software engineers pull out of their toolkits when they encounter a bug or a system failure. It’s a constant, ongoing process that’s intrinsic to every aspect of their work. Let’s break down why this skill is so critical.

Driving Development Forward

Without problem solving, software development would hit a standstill. Every new feature, every optimization, and every bug fix is a problem that needs solving. Whether it’s a performance issue that needs diagnosing or a user interface that needs improving, the capacity to tackle and solve these problems is what keeps the wheels of development turning.

It’s estimated that 60% of software development lifecycle costs are related to maintenance tasks, including debugging and problem solving. This highlights how pivotal this skill is to the everyday functioning and advancement of software systems.

Innovation and Optimization

The importance of problem solving isn’t confined to reactive scenarios; it also plays a major role in proactive, innovative initiatives . Software engineers often need to think outside the box to come up with creative solutions, whether it’s optimizing an algorithm to run faster or designing a new feature to meet customer needs. These are all forms of problem solving.

Consider the development of the modern smartphone. It wasn’t born out of a pre-existing issue but was a solution to a problem people didn’t realize they had — a device that combined communication, entertainment, and productivity into one handheld tool.

Increasing Efficiency and Productivity

Good problem-solving skills can save a lot of time and resources. Effective problem-solvers are adept at dissecting an issue to understand its root cause, thus reducing the time spent on trial and error. This efficiency means projects move faster, releases happen sooner, and businesses stay ahead of their competition.

Improving Software Quality

Problem solving also plays a significant role in enhancing the quality of the end product. By tackling the root causes of bugs and system failures, software engineers can deliver reliable, high-performing software. This is critical because, according to the Consortium for Information and Software Quality, poor quality software in the U.S. in 2022 cost at least $2.41 trillion in operational issues, wasted developer time, and other related problems.

Problem-Solving Techniques in Software Engineering

So how do software engineers go about tackling these complex challenges? Let’s explore some of the key problem-solving techniques, theories, and processes they commonly use.

Decomposition

Breaking down a problem into smaller, manageable parts is one of the first steps in the problem-solving process. It’s like dealing with a complicated puzzle. You don’t try to solve it all at once. Instead, you separate the pieces, group them based on similarities, and then start working on the smaller sets. This method allows software engineers to handle complex issues without being overwhelmed and makes it easier to identify where things might be going wrong.

Abstraction

In the realm of software engineering, abstraction means focusing on the necessary information only and ignoring irrelevant details. It is a way of simplifying complex systems to make them easier to understand and manage. For instance, a software engineer might ignore the details of how a database works to focus on the information it holds and how to retrieve or modify that information.

Algorithmic Thinking

At its core, software engineering is about creating algorithms — step-by-step procedures to solve a problem or accomplish a goal. Algorithmic thinking involves conceiving and expressing these procedures clearly and accurately and viewing every problem through an algorithmic lens. A well-designed algorithm not only solves the problem at hand but also does so efficiently, saving computational resources.

Parallel Thinking

Parallel thinking is a structured process where team members think in the same direction at the same time, allowing for more organized discussion and collaboration. It’s an approach popularized by Edward de Bono with the “ Six Thinking Hats ” technique, where each “hat” represents a different style of thinking.

In the context of software engineering, parallel thinking can be highly effective for problem solving. For instance, when dealing with a complex issue, the team can use the “White Hat” to focus solely on the data and facts about the problem, then the “Black Hat” to consider potential problems with a proposed solution, and so on. This structured approach can lead to more comprehensive analysis and more effective solutions, and it ensures that everyone’s perspectives are considered.

This is the process of identifying and fixing errors in code . Debugging involves carefully reviewing the code, reproducing and analyzing the error, and then making necessary modifications to rectify the problem. It’s a key part of maintaining and improving software quality.

Testing and Validation

Testing is an essential part of problem solving in software engineering. Engineers use a variety of tests to verify that their code works as expected and to uncover any potential issues. These range from unit tests that check individual components of the code to integration tests that ensure the pieces work well together. Validation, on the other hand, ensures that the solution not only works but also fulfills the intended requirements and objectives.

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Evaluating Problem-Solving Skills

We’ve examined the importance of problem-solving in the work of a software engineer and explored various techniques software engineers employ to approach complex challenges. Now, let’s delve into how hiring teams can identify and evaluate problem-solving skills during the hiring process.

Recognizing Problem-Solving Skills in Candidates

How can you tell if a candidate is a good problem solver? Look for these indicators:

• Previous Experience: A history of dealing with complex, challenging projects is often a good sign. Ask the candidate to discuss a difficult problem they faced in a previous role and how they solved it.
• Problem-Solving Questions: During interviews, pose hypothetical scenarios or present real problems your company has faced. Ask candidates to explain how they would tackle these issues. You’re not just looking for a correct solution but the thought process that led them there.
• Technical Tests: Coding challenges and other technical tests can provide insight into a candidate’s problem-solving abilities. Consider leveraging a platform for assessing these skills in a realistic, job-related context.

Assessing Problem-Solving Skills

Once you’ve identified potential problem solvers, here are a few ways you can assess their skills:

• Solution Effectiveness: Did the candidate solve the problem? How efficient and effective is their solution?
• Approach and Process: Go beyond whether or not they solved the problem and examine how they arrived at their solution. Did they break the problem down into manageable parts? Did they consider different perspectives and possibilities?
• Communication: A good problem solver can explain their thought process clearly. Can the candidate effectively communicate how they arrived at their solution and why they chose it?
• Adaptability: Problem-solving often involves a degree of trial and error. How does the candidate handle roadblocks? Do they adapt their approach based on new information or feedback?

Hiring managers play a crucial role in identifying and fostering problem-solving skills within their teams. By focusing on these abilities during the hiring process, companies can build teams that are more capable, innovative, and resilient.

Key Takeaways

As you can see, problem solving plays a pivotal role in software engineering. Far from being an occasional requirement, it is the lifeblood that drives development forward, catalyzes innovation, and delivers of quality software. 

By leveraging problem-solving techniques, software engineers employ a powerful suite of strategies to overcome complex challenges. But mastering these techniques isn’t simple feat. It requires a learning mindset, regular practice, collaboration, reflective thinking, resilience, and a commitment to staying updated with industry trends. 

For hiring managers and team leads, recognizing these skills and fostering a culture that values and nurtures problem solving is key. It’s this emphasis on problem solving that can differentiate an average team from a high-performing one and an ordinary product from an industry-leading one.

At the end of the day, software engineering is fundamentally about solving problems — problems that matter to businesses, to users, and to the wider society. And it’s the proficient problem solvers who stand at the forefront of this dynamic field, turning challenges into opportunities, and ideas into reality.

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AgileEngine Blog > Insights > Why engineers need strong problem-solving skills—and how to ensure your team has them

Why engineers need strong problem-solving skills—and how to ensure your team has them

Table of Contents

Alex Gorlatov

A story about hiring the wrong person.

As a young engineer before joining AgileEngine, I had a co-worker. Let’s call him Dave.

I met Dave when the company interviewed him for a Java development job. His technical interview with us focused on simple, direct questions to assess his knowledge of specific backend technologies, like Java and SQL. He did well, showing strong knowledge of the programming side of backend web development. The company hired him.

But after he came on board, Dave struggled. His managers delegated new web application features for him to implement, expecting him to own the outcomes and deliver. But he often didn’t know where to start his work or how to break it down into manageable tasks for himself. For the work to get done, he needed his specific tasks defined for him. Though he knew the tech, he just couldn’t solve problems on his own.

In his defense, the requirements for these features were not always crystal clear. These vague inputs made Dave’s job harder. Nevertheless, the job description mentioned the need for a person to own such efforts — including elaborating requirements — and such was the company’s expectation.

After a year of low productivity, Dave left the company.

The problem: The gap between technical knowledge and solving unstructured problems

Technology organizations frequently face this challenge. Many engineers intimately know the details of their chosen technologies but fail to solve unstructured problems that cover unfamiliar territory. Such difficulties might involve a bleeding-edge technology, a company-wide business flow, or a novel challenge without an existing pattern to apply.

To overcome these or similar difficulties, engineering teams need broader creative skills to innovate and tackle new problems. 

The solution: Building general problem-solving skills

In my experience, solving complex real-world software engineering problems requires an ability to:

• Define or clarify stakeholders’ desired outcomes
• Identify root causes of difficulties
• Decompose a challenge (or solution) into smaller pieces that are easier to solve (or manage)
• Ideate solutions, both alone and while collaborating with other team members
• Plan and conduct quality assurance

These skills are really about system design in general and do not belong to any single technical domain. Engineers with these broad skills can tackle just about any analytical or engineering difficulty as long as they also have the requisite (and complementary) technical knowledge.

One more observation: while some hard problem-solving skills (e.g., root cause analysis) can be taught via courses or books, the ability described here also depends on things like temperament and aptitude. As with computer programming, a person typically either has a knack for it or doesn’t. Thus, one of the best ways to develop this capacity in your organization is to screen for it when hiring.

Our approach: Evaluate candidates for broad problem-solving during interviews

In remote software engineering engagement models with higher degrees of autonomy and initiative, like dedicated teams or managed projects, problem-solving is critical for success. For this reason, our hiring process involves an evaluation of general problem-solving skills in addition to specific technical knowledge.

At AgileEngine, extensive screening for problem-solving skills is mandatory for senior, lead, or higher engineering positions. We also include it for any seniority level when selecting experts for a dedicated team with a demanding problem-solving culture and a high sense of product ownership.

To evaluate these skills during the candidate’s interview, we present them with an open-ended design challenge that roughly corresponds to their technical specialty. We give them a broad, slightly ambiguous technical problem and ask them to explain how they would go about solving it.

Naturally, we have different expectations for the different seniority levels. We give each candidate a score of 0 to 4 based on the following criteria.

Skills expectations for a junior engineer

• Understands basic requirements and has the ability to ask questions to clarify when needed.

Skills expectations for a middle engineer

• May suggest small or mid-size feature estimates.
• Knows how to split tasks, especially for their tech stack.
• Has analytical thinking skills, breaking down issues to identify causes.
• Can come up with ideas that can be used as a starting point when tackling complex tasks.

Skill expectations for a senior engineer

• Performs discovery for a feature, asking questions and collecting data.
• Organizes the feature breakdown and provides estimations for both backend and frontend.
• Understands what to do if there are no QA engineers on the team.
• Can come up with a strategy to locate the source of the difficulty and can also mention different strategies for solving it.
• Can analyze and discuss trade-offs for proposed solutions.

Skill expectations for a lead engineer

• Has solid experience driving the development of new products from scratch.
• Drives communication with the client to collect functional and non-functional requirements and knows how to initiate and conduct the necessary discovery activities.
• Organizes the feature breakdown and provides estimations.
• Has awareness of the team’s strengths and capabilities.
• Considers time for automated testing and cares about future maintainability and scalability.
• Can diagnose and solve complex problems and help others to solve them.
• Can propose innovative solutions to challenging problems often requiring optimization or efficiency improvements.
• Uses systematic problem-solving methodologies (e.g., root cause analysis, hypothesis testing).

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Our results: correlation between general problem-solving excellence and passing our clients’ interview process.

Since implementing the evaluation in our interviews, we have seen a dramatic increase in client satisfaction with the team members we have brought forward into our engagements. Our candidates who receive top scores for general problem-solving are up to three times more likely to pass the full interview process than those with low scores. The precise difference depends on the technology stack.

Here are the metrics broken down by tech stack or specialization.

In the hiring process for Java engineering roles, AgileEngine’s candidates with higher general problem-solving scores (2 or 3) were twice as likely to be accepted by clients as those with low scores (0).

React.js candidates with higher general problem-solving scores (2, 3, or 4) were roughly three times more likely to be accepted by clients than those with low scores (0 or 1).

Node.js candidates with higher general problem-solving scores (2) were roughly twice as likely to be accepted by clients as those with low scores (0 or 1).

QA engineering candidates with higher general problem-solving scores (3 or 4) were roughly 33% more likely to be accepted by clients than those with low scores (0, 1, or 2).

The evidence above speaks to the significance that companies attach to problem-solving skills when engaging engineering talent. Engineering teams often have to deal with challenges characterized by unclear or changing scope and complexity that goes beyond technology. By prioritizing candidates with strong problem-solving skills, companies can tackle such challenges faster and gain an edge over the competition.

In today’s increasingly competitive and quickly evolving world, you need people who can find innovative solutions to non-trivial challenges. Specific technical skills are often not enough for this — you must find engineers who can analyze, define, and decompose problems that haven’t been solved before.

AgileEngine has vast expertise in ensuring that new members of our clients’ remote teams have this capability. Our approach to candidate selection empowers our clients to create innovative solutions that win awards, get top-rated by the Play Store and App Store, and land top spots on G2 and Gartner. Talk to our experts and explore what positive impact this approach can have on your digital product.

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Alex is a technology executive with a 25-plus-year background as a development manager, scrum master, and software architect. specializing in business process automation, system integration, and custom solutions development, he empowers clients across industries to streamline operations, amplify communication, and optimize it investments for maximum impact., share this post, related articles.

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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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10 Steps to Problem Solving for Engineers

Updated: Dec 6, 2020

With the official launch of the engineering book 10+1 Steps to Problem Solving: An Engineer's Guide it may be interesting to know that formalization of the concept began in episode 2 of the Engineering IRL Podcast back in July 2018.

As noted in the book remnants of the steps had existed throughout my career and in this episode I actually recorded the episode off the top of my head.

My goal was to help engineers build a practical approach to problem solving.

Have a listen.

Who can advise on the best approach to problem solving other than the professional problem solvers - Yes. I'm talking about being an Engineer.

There are 2 main trains of thought with Engineering work for non-engineers and that's trying to change the world with leading edge tech and innovations, or plain old boring math nerd type things.

Whilst, somewhat the case what this means is most content I read around Tech and Engineering are either super technical and (excruciatingly) detailed. OR really riff raff at the high level reveling at the possibilities of changing the world as we know it. And so what we end up with is a base (engineer only details) and the topping (media innovation coverage) but what about the meat? The contents?

There's a lot of beauty and interesting things there too. And what's the centrepiece? The common ground between all engineers? Problem solving.

The number one thing an Engineer does is problem solving. Now you may say, "hey, that's the same as my profession" - well this would be true for virtually every single profession on earth. This is not saying there isn't problem solving required in other professions. Some problems require very basic problem solving techniques such is used in every day life, but sometimes problems get more complicated, maybe they involve other parties, maybe its a specific quirk of the system in a specific scenario. One thing you learn in engineering is that not all problems are equal. These are

 The stages of problem solving like a pro:

Is the problem identified (no, really, are you actually asking the right question?)

Have you applied related troubleshooting step to above problem?

Have you applied basic troubleshooting steps (i.e. check if its plugged in, turned it on and off again, checked your basics)

Tried step 2 again? (Desperation seeps in, but check your bases)

Asked a colleague or someone else that may have dealt with your problem? (50/50 at this point)

Asked DR. Google (This is still ok)

Deployed RTFM protocol (Read the F***ing Manual - Engineers are notorious for not doing this)

Repeated tests, changing slight things, checking relation to time, or number of people, or location or environment (we are getting DEEP now)

Go to the bottom level, in networking this is packet sniffers to inspect packets, in systems this is taking systems apart and testing in isolation, in software this is checking if 1 equals 1, you are trying to prove basic human facts that everyone knows. If 1 is not equal to 1, you're in deep trouble.At this point you are at rebuild from scratch, re install, start again as your answer (extremely expensive, very rare)

And there you have it! Those are your levels of problem solving. As you go through each step, the more expensive the problem is. -- BUT WAIT. I picked something up along the way and this is where I typically thrive. Somewhere between problem solving step 8 and 10. 

The secret step

My recommendation at this point is to try tests that are seemingly unrelated to anything to do with the problem at all.Pull a random cable, test with a random system off/on, try it at a specific time of the day, try it specifically after restarting or replugging something in. Now, not completely random but within some sort of scope. These test are the ones that when someone is having a problem when you suggest they say "that shouldn't fix the problem, that shouldn't be related" and they are absolutely correct.But here's the thing -- at this stage they have already tried everything that SHOULD fix the problem. Now it's time for the hail mary's, the long shots, the clutching at straws. This method works wonders for many reasons. 1. You really are trying to try "anything" at this point.

2. Most of the time we may think we have problem solving step number 1 covered, but we really don't.

3. Triggering correlations.

This is important.

Triggering correlations

In a later post I will cover correlation vs causation, but for now understand that sometimes all you want to do is throw in new inputs to the system or problem you are solving in order to get clues or re identify problems or give new ways to approach earlier problem solving steps. There you have it. Problem solve like a ninja. Approach that extremely experienced and smart person what their problem and as they describe all the things they've tried, throw in a random thing they haven't tried. And when they say, well that shouldn't fix it, you ask them, well if you've exhausted everything that should  have worked, this is the time to try things that shouldn't. Either they will think of more tests they haven't considered so as to avoid doing your preposterous idea OR they try it and get a new clue to their problem. Heck, at worst they confirm that they do know SOMETHING about the system.

Go out and problem solve ! As always, thanks for reading and good luck with all of your side hustles.

If you prefer to listen to learn we got you covered with the Engineering IRL show!

For Youtube please go to:

https://youtu.be/EHaRNZhqmHA

For Spotify please go to:

https://open.spotify.com/show/3UZPfOvNwQkaCA1jLIOxp4

And don't forget to subscribe if you get any value from the Engineering IRL Content

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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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