importance of problem solving in programming

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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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.

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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.

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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.

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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.

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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.

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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.

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Step 5 – Implement

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

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

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

Step 6 – Evaluate

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

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

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

Final Thoughts

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

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

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

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

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

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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

Tutorial Playlist

Programming tutorial, your guide to the best backend languages for 2024, an ultimate guide that helps you to start learn coding 2024, what is backend development: the ultimate guide for beginners, all you need to know for choosing the first programming language to learn, here’s all you need to know about coding, decoding, and reasoning with examples, understanding what is xml: the best guide to xml and its concepts., an ultimate guide to learn the importance of low-code and no-code development, top frontend languages that you should know about, top 75+ frontend developer interview questions and answers, the ultimate guide to learn typescript generics, the most comprehensive guide for beginners to know ‘what is typescript’.

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Most commonly asked logical reasoning questions in an aptitude test, everything you need to know about advanced typescript concepts, an absolute guide to build c hello world program, a one-stop solution guide to learn how to create a game in unity, what is nat significance of nat for translating ip addresses in the network model, data science vs software engineering: key differences, a real-time chat application typescript project using node.js as a server, what is raspberry pi here’s the best guide to get started, what is arduino here’s the best beginners guide to get started, arduino vs. raspberry pi: which is the better board, the perfect guide for all you need to learn about mean stack, software developer resume: a comprehensive guide, here’s everything all you need to know about the programming roadmap, an ultimate guide that helps you to develop and improve problem solving in programming, the top 10 awesome arduino projects of all time, roles of product managers, pyspark rdd: everything you need to know about pyspark rdd, wipro interview questions and answers that you should know before going for an interview, how to use typescript with nodejs: the ultimate guide, what is rust programming language why is it so popular, software terminologies, an ultimate guide that helps you to develop and improve problem solving in programming.

Lesson 27 of 34 By Hemant Deshpande

Table of Contents

Coding and Programming skills hold a significant and critical role in implementing and developing various technologies and software. They add more value to the future and development. These programming and coding skills are essential for every person to improve problem solving skills. So, we brought you this article to help you learn and know the importance of these skills in the future. 

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Topics covered in this problem solving in programming article are:

• What is Problem Solving in Programming? 
• Problem Solving skills in Programming
• How does it impact your career ?
• Steps involved in Problem Solving
• Steps to improve Problem Solving in programming

What is Problem Solving in Programming?

Computers are used to solve various problems in day-to-day life. Problem Solving is an essential skill that helps to solve problems in programming. There are specific steps to be carried out to solve problems in computer programming, and the success depends on how correctly and precisely we define a problem. This involves designing, identifying and implementing problems using certain steps to develop a computer.

When we know what exactly problem solving in programming is, let us learn how it impacts your career growth.

How Does It Impact Your Career?

Many companies look for candidates with excellent problem solving skills. These skills help people manage the work and make candidates put more effort into the work, which results in finding solutions for complex problems in unexpected situations. These skills also help to identify quick solutions when they arise and are identified. 

People with great problem solving skills also possess more thinking and analytical skills, which makes them much more successful and confident in their career and able to work in any kind of environment. 

The above section gives you an idea of how problem solving in programming impacts your career and growth. Now, let's understand what problem solving skills mean.

Problem Solving Skills in Programming

Solving a question that is related to computers is more complicated than finding the solutions for other questions. It requires excellent knowledge and much thinking power. Problem solving in programming skills is much needed for a person and holds a major advantage. For every question, there are specific steps to be followed to get a perfect solution. By using those steps, it is possible to find a solution quickly.

The above section is covered with an explanation of problem solving in programming skills. Now let's learn some steps involved in problem solving.

Steps Involved in Problem Solving

Before being ready to solve a problem, there are some steps and procedures to be followed to find the solution. Let's have a look at them in this problem solving in programming article.

Basically, they are divided into four categories:

• Analysing the problem
• Developing the algorithm
• Testing and debugging

Analysing the Problem

Every problem has a perfect solution; before we are ready to solve a problem, we must look over the question and understand it. When we know the question, it is easy to find the solution for it. If we are not ready with what we have to solve, then we end up with the question and cannot find the answer as expected. By analysing it, we can figure out the outputs and inputs to be carried out. Thus, when we analyse and are ready with the list, it is easy and helps us find the solution easily. 

Developing the Algorithm

It is required to decide a solution before writing a program. The procedure of representing the solution  in a natural language called an algorithm. We must design, develop and decide the final approach after a number of trials and errors, before actually writing the final code on an algorithm before we write the code. It captures and refines all the aspects of the desired solution.

Once we finalise the algorithm, we must convert the decided algorithm into a code or program using a dedicated programming language that is understandable by the computer to find a desired solution. In this stage, a wide variety of programming languages are used to convert the algorithm into code. 

Testing and Debugging

The designed and developed program undergoes several rigorous tests based on various real-time parameters and the program undergoes various levels of simulations. It must meet the user's requirements, which have to respond with the required time. It should generate all expected outputs to all the possible inputs. The program should also undergo bug fixing and all possible exception handling. If it fails to show the possible results, it should be checked for logical errors.

Industries follow some testing methods like system testing, component testing and acceptance testing while developing complex applications. The errors identified while testing are debugged or rectified and tested again until all errors are removed from the program.

The steps mentioned above are involved in problem solving in programming. Now let's see some more detailed information about the steps to improve problem solving in programming.

Steps to Improve Problem Solving in Programming

Right mindset.

The way to approach problems is the key to improving the skills. To find a solution, a positive mindset helps to solve problems quickly. If you think something is impossible, then it is hard to achieve. When you feel free and focus with a positive attitude, even complex problems will have a perfect solution.

Making Right Decisions

When we need to solve a problem, we must be clear with the solution. The perfect solution helps to get success in a shorter period. Making the right decisions in the right situation helps to find the perfect solution quickly and efficiently. These skills also help to get more command over the subject.

Keeping Ideas on Track

Ideas always help much in improving the skills; they also help to gain more knowledge and more command over things. In problem solving situations, these ideas help much and help to develop more skills. Give opportunities for the mind and keep on noting the ideas.

Learning from Feedbacks

A crucial part of learning is from the feedback. Mistakes help you to gain more knowledge and have much growth. When you have a solution for a problem, go for the feedback from the experienced or the professionals. It helps you get success within a shorter period and enables you to find other solutions easily.

Asking Questions

Questions are an incredible part of life. While searching for solutions, there are a lot of questions that arise in our minds. Once you know the question correctly, then you are able to find answers quickly. In coding or programming, we must have a clear idea about the problem. Then, you can find the perfect solution for it. Raising questions can help to understand the problem.

These are a few reasons and tips to improve problem solving in programming skills. Now let's see some major benefits in this article.

• Problem solving in programming skills helps to gain more knowledge over coding and programming, which is a major benefit.
• These problem solving skills also help to develop more skills in a person and build a promising career.
• These skills also help to find the solutions for critical and complex problems in a perfect way.
• Learning and developing problem solving in programming helps in building a good foundation.
• Most of the companies are looking for people with good problem solving skills, and these play an important role when it comes to job opportunities 

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Problem solving in programming skills is important in this modern world; these skills build a great career and hold a great advantage. This article on problem solving in programming provides you with an idea of how it plays a massive role in the present world. In this problem solving in programming article, the skills and the ways to improve more command on problem solving in programming are mentioned and explained in a proper way.

If you are looking to advance in your career. Simplilearn provides training and certification courses on various programming languages - Python , Java , Javascript , and many more. Check out our Post Graduate Program in Full Stack Web Development course that will help you excel in your career.

If you have any questions for us on the problem solving in programming article. Do let us know in the comments section below; we have our experts answer it right away.

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About the author.

Hemant Deshpande, PMP has more than 17 years of experience working for various global MNC's. He has more than 10 years of experience in managing large transformation programs for Fortune 500 clients across verticals such as Banking, Finance, Insurance, Healthcare, Telecom and others. During his career he has worked across the geographies - North America, Europe, Middle East, and Asia Pacific. Hemant is an internationally Certified Executive Coach (CCA/ICF Approved) working with corporate leaders. He also provides Management Consulting and Training services. He is passionate about writing and regularly blogs and writes content for top websites. His motto in life - Making a positive difference.

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• PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.

Problem Solving

Foundations course, introduction.

Before we start digging into some pretty nifty JavaScript, we need to begin talking about problem solving : the most important skill a developer needs.

Problem solving is the core thing software developers do. The programming languages and tools they use are secondary to this fundamental skill.

From his book, “Think Like a Programmer” , V. Anton Spraul defines problem solving in programming as:

Problem solving is writing an original program that performs a particular set of tasks and meets all stated constraints.

The set of tasks can range from solving small coding exercises all the way up to building a social network site like Facebook or a search engine like Google. Each problem has its own set of constraints, for example, high performance and scalability may not matter too much in a coding exercise but it will be vital in apps like Google that need to service billions of search queries each day.

New programmers often find problem solving the hardest skill to build. It’s not uncommon for budding programmers to breeze through learning syntax and programming concepts, yet when trying to code something on their own, they find themselves staring blankly at their text editor not knowing where to start.

The best way to improve your problem solving ability is by building experience by making lots and lots of programs. The more practice you have the better you’ll be prepared to solve real world problems.

In this lesson we will walk through a few techniques that can be used to help with the problem solving process.

Lesson overview

This section contains a general overview of topics that you will learn in this lesson.

• Explain the three steps in the problem solving process.
• Explain what pseudocode is and be able to use it to solve problems.
• Be able to break a problem down into subproblems.

Understand the problem

The first step to solving a problem is understanding exactly what the problem is. If you don’t understand the problem, you won’t know when you’ve successfully solved it and may waste a lot of time on a wrong solution .

To gain clarity and understanding of the problem, write it down on paper, reword it in plain English until it makes sense to you, and draw diagrams if that helps. When you can explain the problem to someone else in plain English, you understand it.

Now that you know what you’re aiming to solve, don’t jump into coding just yet. It’s time to plan out how you’re going to solve it first. Some of the questions you should answer at this stage of the process:

• Does your program have a user interface? What will it look like? What functionality will the interface have? Sketch this out on paper.
• What inputs will your program have? Will the user enter data or will you get input from somewhere else?
• What’s the desired output?
• Given your inputs, what are the steps necessary to return the desired output?

The last question is where you will write out an algorithm to solve the problem. You can think of an algorithm as a recipe for solving a particular problem. It defines the steps that need to be taken by the computer to solve a problem in pseudocode.

Pseudocode is writing out the logic for your program in natural language instead of code. It helps you slow down and think through the steps your program will have to go through to solve the problem.

Here’s an example of what the pseudocode for a program that prints all numbers up to an inputted number might look like:

This is a basic program to demonstrate how pseudocode looks. There will be more examples of pseudocode included in the assignments.

Divide and conquer

From your planning, you should have identified some subproblems of the big problem you’re solving. Each of the steps in the algorithm we wrote out in the last section are subproblems. Pick the smallest or simplest one and start there with coding.

It’s important to remember that you might not know all the steps that you might need up front, so your algorithm may be incomplete -— this is fine. Getting started with and solving one of the subproblems you have identified in the planning stage often reveals the next subproblem you can work on. Or, if you already know the next subproblem, it’s often simpler with the first subproblem solved.

Many beginners try to solve the big problem in one go. Don’t do this . If the problem is sufficiently complex, you’ll get yourself tied in knots and make life a lot harder for yourself. Decomposing problems into smaller and easier to solve subproblems is a much better approach. Decomposition is the main way to deal with complexity, making problems easier and more approachable to solve and understand.

In short, break the big problem down and solve each of the smaller problems until you’ve solved the big problem.

Solving Fizz Buzz

To demonstrate this workflow in action, let’s solve a common programming exercise: Fizz Buzz, explained in this wiki article .

Understanding the problem

Write a program that takes a user’s input and prints the numbers from one to the number the user entered. However, for multiples of three print Fizz instead of the number and for the multiples of five print Buzz . For numbers which are multiples of both three and five print FizzBuzz .

This is the big picture problem we will be solving. But we can always make it clearer by rewording it.

Write a program that allows the user to enter a number, print each number between one and the number the user entered, but for numbers that divide by 3 without a remainder print Fizz instead. For numbers that divide by 5 without a remainder print Buzz and finally for numbers that divide by both 3 and 5 without a remainder print FizzBuzz .

Does your program have an interface? What will it look like? Our FizzBuzz solution will be a browser console program, so we don’t need an interface. The only user interaction will be allowing users to enter a number.

What inputs will your program have? Will the user enter data or will you get input from somewhere else? The user will enter a number from a prompt (popup box).

What’s the desired output? The desired output is a list of numbers from 1 to the number the user entered. But each number that is divisible by 3 will output Fizz , each number that is divisible by 5 will output Buzz and each number that is divisible by both 3 and 5 will output FizzBuzz .

Writing the pseudocode

What are the steps necessary to return the desired output? Here is an algorithm in pseudocode for this problem:

Dividing and conquering

As we can see from the algorithm we developed, the first subproblem we can solve is getting input from the user. So let’s start there and verify it works by printing the entered number.

With JavaScript, we’ll use the “prompt” method.

The above code should create a little popup box that asks the user for a number. The input we get back will be stored in our variable answer .

We wrapped the prompt call in a parseInt function so that a number is returned from the user’s input.

With that done, let’s move on to the next subproblem: “Loop from 1 to the entered number”. There are many ways to do this in JavaScript. One of the common ways - that you actually see in many other languages like Java, C++, and Ruby - is with the for loop :

If you haven’t seen this before and it looks strange, it’s actually straightforward. We declare a variable i and assign it 1: the initial value of the variable i in our loop. The second clause, i <= answer is our condition. We want to loop until i is greater than answer . The third clause, i++ , tells our loop to increment i by 1 every iteration. As a result, if the user inputs 10, this loop would print numbers 1 - 10 to the console.

Most of the time, programmers find themselves looping from 0. Due to the needs of our program, we’re starting from 1

With that working, let’s move on to the next problem: If the current number is divisible by 3, then print Fizz .

We are using the modulus operator ( % ) here to divide the current number by three. If you recall from a previous lesson, the modulus operator returns the remainder of a division. So if a remainder of 0 is returned from the division, it means the current number is divisible by 3.

After this change the program will now output this when you run it and the user inputs 10:

The program is starting to take shape. The final few subproblems should be easy to solve as the basic structure is in place and they are just different variations of the condition we’ve already got in place. Let’s tackle the next one: If the current number is divisible by 5 then print Buzz .

When you run the program now, you should see this output if the user inputs 10:

We have one more subproblem to solve to complete the program: If the current number is divisible by 3 and 5 then print FizzBuzz .

We’ve had to move the conditionals around a little to get it to work. The first condition now checks if i is divisible by 3 and 5 instead of checking if i is just divisible by 3. We’ve had to do this because if we kept it the way it was, it would run the first condition if (i % 3 === 0) , so that if i was divisible by 3, it would print Fizz and then move on to the next number in the iteration, even if i was divisible by 5 as well.

With the condition if (i % 3 === 0 && i % 5 === 0) coming first, we check that i is divisible by both 3 and 5 before moving on to check if it is divisible by 3 or 5 individually in the else if conditions.

The program is now complete! If you run it now you should get this output when the user inputs 20:

• Read How to Think Like a Programmer - Lessons in Problem Solving by Richard Reis.
• Watch How to Begin Thinking Like a Programmer by Coding Tech. It’s an hour long but packed full of information and definitely worth your time watching.
• Read this Pseudocode: What It Is and How to Write It article from Built In.

Knowledge check

This section contains questions for you to check your understanding of this lesson on your own. If you’re having trouble answering a question, click it and review the material it links to.

• What are the three stages in the problem solving process?
• Why is it important to clearly understand the problem first?
• What can you do to help get a clearer understanding of the problem?
• What are some of the things you should do in the planning stage of the problem solving process?
• What is an algorithm?
• What is pseudocode?
• What are the advantages of breaking a problem down and solving the smaller problems?

Additional resources

This section contains helpful links to other content. It isn’t required, so consider it supplemental.

• Read the first chapter in Think Like a Programmer: An Introduction to Creative Problem Solving ( not free ). This book’s examples are in C++, but you will understand everything since the main idea of the book is to teach programmers to better solve problems. It’s an amazing book and worth every penny. It will make you a better programmer.
• Watch this video on repetitive programming techniques .
• Watch Jonathan Blow on solving hard problems where he gives sage advice on how to approach problem solving in software projects.

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How to Solve Coding Problems with a Simple Four Step Method

I had fifteen minutes left, and I knew I was going to fail.

I had spent two months studying for my first technical interview.

I thought I was prepared, but as the interview came to a close, it hit me: I had no idea how to solve coding problems.

Of all the tutorials I had taken when I was learning to code, not one of them had included an approach to solving coding problems.

I had to find a method for problem-solving—my career as a developer depended on it.

I immediately began researching methods. And I found one. In fact, what I uncovered was an invaluable strategy. It was a time-tested four-step method that was somehow under the radar in the developer ecosystem.

In this article, I’ll go over this four-step problem-solving method that you can use to start confidently solving coding problems.

Solving coding problems is not only part of the developer job interview process—it’s what a developer does all day. After all, writing code is problem-solving.

A method for solving problems

This method is from the book How to Solve It by George Pólya. It originally came out in 1945 and has sold over one million copies.

His problem-solving method has been used and taught by many programmers, from computer science professors (see Udacity’s Intro to CS course taught by professor David Evans) to modern web development teachers like Colt Steele.

Let’s walk through solving a simple coding problem using the four-step problem-solving method. This allows us to see the method in action as we learn it. We'll use JavaScript as our language of choice. Here’s the problem:

Create a function that adds together two numbers and returns that value. There are four steps to the problem-solving method:

• Understand the problem.
• Devise a plan.
• Carry out the plan.

Let’s get started with step one.

Step 1: Understand the problem.

When given a coding problem in an interview, it’s tempting to rush into coding. This is hard to avoid, especially if you have a time limit.

However, try to resist this urge. Make sure you actually understand the problem before you get started with solving it.

Read through the problem. If you’re in an interview, you could read through the problem out loud if that helps you slow down.

As you read through the problem, clarify any part of it you do not understand. If you’re in an interview, you can do this by asking your interviewer questions about the problem description. If you’re on your own, think through and/or Google parts of the question you might not understand.

This first step is vital as we often don’t take the time to fully understand the problem. When you don’t fully understand the problem, you’ll have a much harder time solving it.

To help you better understand the problem, ask yourself:

What are the inputs?

What kinds of inputs will go into this problem? In this example, the inputs are the arguments that our function will take.

Just from reading the problem description so far, we know that the inputs will be numbers. But to be more specific about what the inputs will be, we can ask:

Will the inputs always be just two numbers? What should happen if our function receives as input three numbers?

Here we could ask the interviewer for clarification, or look at the problem description further.

The coding problem might have a note saying, “You should only ever expect two inputs into the function.” If so, you know how to proceed. You can get more specific, as you’ll likely realize that you need to ask more questions on what kinds of inputs you might be receiving.

Will the inputs always be numbers? What should our function do if we receive the inputs “a” and “b”? Clarify whether or not our function will always take in numbers.

Optionally, you could write down possible inputs in a code comment to get a sense of what they’ll look like:

//inputs: 2, 4

What are the outputs?

What will this function return? In this case, the output will be one number that is the result of the two number inputs. Make sure you understand what your outputs will be.

Create some examples.

Once you have a grasp of the problem and know the possible inputs and outputs, you can start working on some concrete examples.

Examples can also be used as sanity checks to test your eventual problem. Most code challenge editors that you’ll work in (whether it’s in an interview or just using a site like Codewars or HackerRank) have examples or test cases already written for you. Even so, writing out your own examples can help you cement your understanding of the problem.

Start with a simple example or two of possible inputs and outputs. Let's return to our addition function.

Let’s call our function “add.”

What’s an example input? Example input might be:

// add(2, 3)

What is the output to this? To write the example output, we can write:

// add(2, 3) ---> 5

This indicates that our function will take in an input of 2 and 3 and return 5 as its output.

Create complex examples.

By walking through more complex examples, you can take the time to look for edge cases you might need to account for.

For example, what should we do if our inputs are strings instead of numbers? What if we have as input two strings, for example, add('a', 'b')?

Your interviewer might possibly tell you to return an error message if there are any inputs that are not numbers. If so, you can add a code comment to handle this case if it helps you remember you need to do this.

Your interviewer might also tell you to assume that your inputs will always be numbers, in which case you don’t need to write any extra code to handle this particular input edge case.

If you don’t have an interviewer and you’re just solving this problem, the problem might say what happens when you enter invalid inputs.

For example, some problems will say, “If there are zero inputs, return undefined.” For cases like this, you can optionally write a comment.

// check if there are no inputs.

// If no inputs, return undefined.

For our purposes, we’ll assume that our inputs will always be numbers. But generally, it’s good to think about edge cases.

Computer science professor Evans says to write what developers call defensive code. Think about what could go wrong and how your code could defend against possible errors.  

Before we move on to step 2, let’s summarize step 1, understand the problem:

-Read through the problem.

-What are the inputs?

-What are the outputs?

Create simple examples, then create more complex ones.

2. Devise a plan for solving the problem.

Next, devise a plan for how you’ll solve the problem. As you devise a plan, write it out in pseudocode.

Pseudocode is a plain language description of the steps in an algorithm. In other words, your pseudocode is your step-by-step plan for how to solve the problem.

Write out the steps you need to take to solve the problem. For a more complicated problem, you’d have more steps. For this problem, you could write:

// Create a sum variable.

Add the first input to the second input using the addition operator .

// Store value of both inputs into sum variable.

// Return as output the sum variable. Now you have your step-by-step plan to solve the problem. For more complex problems, professor Evans notes, “Consider systematically how a human solves the problem.” That is, forget about how your code might solve the problem for a moment, and think about how you would solve it as a human. This can help you see the steps more clearly.

3. Carry out the plan (Solve the problem!)

The next step in the problem-solving strategy is to solve the problem. Using your pseudocode as your guide, write out your actual code.

Professor Evans suggests focusing on a simple, mechanical solution. The easier and simpler your solution is, the more likely you can program it correctly.

Taking our pseudocode, we could now write this:

Professor Evans adds, remember not to prematurely optimize. That is, you might be tempted to start saying, “Wait, I’m doing this and it’s going to be inefficient code!”

First, just get out your simple, mechanical solution.

What if you can’t solve the entire problem? What if there's a part of it you still don't know how to solve?

Colt Steele gives great advice here: If you can’t solve part of the problem, ignore that hard part that’s tripping you up. Instead, focus on everything else that you can start writing.

Temporarily ignore that difficult part of the problem you don’t quite understand and write out the other parts. Once this is done, come back to the harder part.

This allows you to get at least some of the problem finished. And often, you’ll realize how to tackle that harder part of the problem once you come back to it.

Step 4: Look back over what you've done.

Once your solution is working, take the time to reflect on it and figure out how to make improvements. This might be the time you refactor your solution into a more efficient one.

As you look at your work, here are some questions Colt Steele suggests you ask yourself to figure out how you can improve your solution:

• Can you derive the result differently? What other approaches are there that are viable?
• Can you understand it at a glance? Does it make sense?
• Can you use the result or method for some other problem?
• Can you improve the performance of your solution?
• Can you think of other ways to refactor?
• How have other people solved this problem?

One way we might refactor our problem to make our code more concise: removing our variable and using an implicit return:

With step 4, your problem might never feel finished. Even great developers still write code that they later look at and want to change. These are guiding questions that can help you.

If you still have time in an interview, you can go through this step and make your solution better. If you are coding on your own, take the time to go over these steps.

When I’m practicing coding on my own, I almost always look at the solutions out there that are more elegant or effective than what I’ve come up with.

Wrapping Up

In this post, we’ve gone over the four-step problem-solving strategy for solving coding problems.

Let's review them here:

• Step 1: understand the problem.
• Step 2: create a step-by-step plan for how you’ll solve it .
• Step 3: carry out the plan and write the actual code.
• Step 4: look back and possibly refactor your solution if it could be better.

Practicing this problem-solving method has immensely helped me in my technical interviews and in my job as a developer. If you don't feel confident when it comes to solving coding problems, just remember that problem-solving is a skill that anyone can get better at with time and practice.

If you enjoyed this post, join my coding club , where we tackle coding challenges together every Sunday and support each other as we learn new technologies.

If you have feedback or questions on this post, feel free to tweet me @madisonkanna ..

Read more posts .

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Blog / Time To Code / 6 Ways to Improve Your Programming Problem Solving

6 Ways to Improve Your Programming Problem Solving

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Software development is, at its core, all about problem solving.

Think about it.

First, developers need to find a problem they can solve with software. Then, they have to figure out how humans solve that problem. And then, they have to find a way to effectively translate both the problem and the solution into code that a computer can use to solve the problem as well as (or better than) a person.

And then there are all the problems along the way: Working with teams, finding and fixing bugs, meeting delivery deadlines.

Engineers use problem solving skills constantly .

Because of that, if you want to become a better developer, one place to start might be becoming a better problem solver. But that’s easier said than done, and requires a deep understanding of what problem solving is, why it matters, and what it actually takes to improve those skills.

Ready to dive in? Let’s get started.

What Is Problem Solving, and Why Does It Matter?

Have you ever heard this famous Steve Jobs quote?

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

Jobs was right. Software development is as much about “soft skills” like critical thinking, communication, and problem solving as it is about “hard skills” like writing code.

And so, in the context of software development, problem solving can mean a few different things:

• Creating an application that meets the end user’s goals.
• Communicating effectively with team members to delegate work.
• Finding and fixing bugs in the code.
• Meeting a tight deadline for a client.

There’s only one thing that’s true no matter what problem solving looks like on a given day: It’s an integral part of every step of the software development process.

Why Should Engineers Work On Problem Solving Skills?

Just like any other skill, problem solving takes practice to apply and master.

Many developers think that becoming a better problem solver means being able to solve more problems, faster. But that’s not true — it means being able to find the best solution to a problem, and then put that solution in place.

Learning to do that is a great way to become a better developer overall. And while soft skills can be more difficult to learn and improve upon than hard skills, there are still some tips and tricks that can help you get better at problem solving specifically.

6 Ways to Get Better at Problem Solving

As you’ll see from these learning tools, getting better at problem solving is mostly like getting better at any other skill for work: You need to practice. A lot. And then practice some more.

Solve a Lot of Problems on a Lot of Different Platforms

Step one? Solve as many problems as you can, but try to focus on different types of problems on different platforms.

Here’s why this is so beneficial: It prevents you from getting comfortable with one problem solving method or framework. As we already know, in the world of software development, there is definitely no one-size-fits-all solution for the problems we encounter.

When you regularly practice solving different types of problems in different platforms, it reinforces the fact that you can’t always rely on the same technique to solve every problem. It forces you to learn to be flexible, and to choose the best tool or framework for each job.

Solve Problems in Contexts Other Than Work

Since problem solving is a skill that requires practice, you can (and should) work on it even outside of work hours.

This doesn’t need to be a chore — there are a lot of fun ways to practice problem solving, like by doing math or logic puzzles, solving crosswords, or playing a game like chess. Even many video games can help work on problem solving skills.

There are also many opportunities to practice problem solving just as you live your life from day to day. Broke something around the house? Use your problem solving skills to DIY a fix. Need to solve a conflict with a friend or a family member? You guessed it — time to practice problem solving.

Learn From Past Solutions, and Apply Them to New Problems

As you keep practicing problem solving as much as possible, you’ll start to see patterns emerge in the problems you solve. You’ll build up a sort of toolkit filled with the solutions you’ve found and used in the past, and you’ll be able to apply those to solving new problems.

This part is just as important as finding the solutions in the first place, because the more you practice your growing problem solving skills, the more natural it will become to apply the right solutions to different types of problems, making you able to solve new problems more and more quickly, while still using the best possible solves.

Ask Others for Help and Feedback

Sometimes, finding the best solution to a problem just requires a fresh, new set of eyes. That’s why it’s important to treat growing your problem solving skills not as a totally solo venture, but as a team endeavor where everyone at your organization can support each other and help each other get better.

If you’re stuck on a specific problem, ask for help. Someone else might have a method or framework you aren’t familiar with, that they can teach you. You can then apply that to more problems down the road.

And if you’ve come up with a solve for a problem, ask others for feedback. They might be able to help you refine or further improve your framework, making it even better.

Train the Problem Solving Part of Your Mind

How do you keep muscles from growing weaker over time? You keep exercising them.

The same goes for your brain, and especially for different knowledge-base skills, like problem solving. You’ll stay at the top of your brain if you keep “working out,” or practicing problem solving all the time.

A good move for a developer who wants to invest in their problem solving skills is scheduling time every week (or even every day) to consciously practice problem solving. Remember, this doesn’t necessarily mean solving work problems. You could commit to doing a tricky logic puzzle every day on your lunch break, for example. The important thing is to get in the practice, no matter how that looks.

Practice Other Skills Related to Problem Solving

Problem solving is an important skill on its own. But there are other necessary skills developers need to support their problem solving abilities, and those skills all take practice, too.

Flexibility. Critical thinking. Communication. Teamwork. Focusing on building and practicing all these skills will help you improve your problem solving.

Problem solving is one of the most necessary skills for developers to have. With time, practice, and dedication, they can improve it, constantly, and keep becoming better.

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Great article regarding problem solving skill, informative and motivating both.

Codility Tests

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Technical Screening Tools

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Sharifa Ismail Yusuf

I learnt from this article that one of the key skills a developer need to have is the \"problem solving skills\". Developers also need dedication, time, create time to practice so they can improve their problem solving skills constantly. I do ask for help from others and learn from past solutions and apply them to new problems. From what I have learnt so far, I will try my best to start focusing on building and practicing Flexibility, critical thinking, communication and team work. Solve a lot of problems on a lot of different platforms. Solve problems on context other than work. To start carring out the above, I will schedule time in a week or everyday to conciously practice problem solving skills and other related problem solving skills.Thanks alot for this wonderful article!

dewayne sewell

Ive learnt the skill of problem solving is like a muscle, where it is important to keep exercising it to stay strong. It is important to be aware of the soft skills necessary for effective problem solving also, such as communication, critical thinking, team working that can leverage your technical hard skills to find a solution faster/more effective. Two things I will aim to do is; 1. To solve problems on different platforms so I don’t get too comfortable on only one and stagnate. This not only challenges the brain to see things from a new perspective, but to start the habit of continuous learning and skill building. 2. Reach out to others for help / discuss problems and my solutions for feedback and advice and sharing ideas.

Pakize Bozkurt

Problem solving skills is a crucial thing to make easier or better your life. In fact as a human being we do it in every day life. I mean, we have to do it for living. There are many ways to how to do it. The best way is we should ask right questions. First of all, we should ask some questions, such as; \' Are we aware of the problem?, Are we clarify the problem? Do we go into problem rational? Do we have reasons? or Do we have evidences? Do we do check them out? etc. I am from Philosophy teacher background. I like solving problem whatever in my work or daily life. Secondly, we should have more perspectives . Although our brain is lazy, it is always in a starvation for knowledge.For this there are many enjoyable things to do it. I highly recommend to read book every day which kind of you like it and playing game or solving puzzle. I love solving Sudoku, puzzle and reading book or article. Finally, solving problem is our invatiable needed. Having flexibility, critical thinking, communication and teamwork are easy way to improve us to how we can do our work better and good life. Massive thank for this amazing article!

I read this amazing article. Normally, everyone knows that but we dont use most of time this informations. Which one is the best way to use? Really it does not matter, every one is like a gold opinion. We can use this ideas for the daily life. I have already used that learn from past solution and ask to someone who knows very well. This is so helpful for me. Sometimes google is the best option for ask to someone. Google can be the best teacher for us as well. Soft skills like a team work or solving problem and critical thinking can be important than typing code. We can learn typing code but we can not learn critical thinking and solving problems from google very well. Thank you for this article.

Ipsa iure sed rerum

Excepturi quo volupt

Thanks for this !

Fahil kiima

Thanks a lot for the ideas on problem solving,I really had a problem with that and now going to use what you\'ve informed us about to better my problem solving skills. Thanks.

Alan Codinho

Nice overview

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Programming is Problem Solving

January 13, 2020

My first full-time job was teaching wilderness survival to adjudicated youth in the deserts of Utah. Though the technologies were primitive, I learned one fundamental skill that I carried throughout my career: the ability to break complicated processes down into simple steps. Starting a fire with bow and drill is not so different from handling asynchronous HTTP requests. To become a lifelong learner, problem solving is the most important skill any individual can develop.

Want to level up your problem solving skills? I write a weekly newsletter about programming, problem solving and lifelong learning. Join now

What Problems Does Programming Solve?

We can distill programming-related problems into two categories:

With algorithms, our goal is to find the most efficient way to perform an operation, such as sorting or searching. With automation, our goal is to find a way to repeatedly perform an operation, such as processing a dataset or dynamically rendering HTML. In many regards, algorithms and automation are one and the same problem.

What is Programming?

Programming is the act and art of writing instructions to be executed by a machine. These instructions must follow a predetermined, formalized , set of rules. These rules determine what we can write and how we can use those whats. A programming language is, fundamentally, a combination of logic and syntax, or a set of instructions for writing instructions. So meta!

One of the biggest challenges in learning to program is making the transition from natural language to formal language , or, learning to think like a computer. Why don’t we learn procedural thinking from daily life? Giving directions or following a recipe are exercises in procedural thinking, “[b]ut in everyday life, procedures are lived and used, they are not necessarily reflected on.” Programming is a metacognitive activity. To be successful, we need to improve our ability to think about thinking .

What is Problem Solving?

According to Wikipedia, problem solving …

…consists of using generic or ad hoc methods in an orderly manner to find solutions to problems.

Sounds a lot like programming, doesn’t it?

In the classic How To Solve It , George Polya outlines a methodology for problem-solving in the context of mathematics. We can easily apply it to programming. Polya’s heuristics can be distilled into four ordinate categories, each with specific questions to ask:

• Understand the Problem : What is the problem? What is the goal? Describe the issue or bug. What is the console or terminal telling you? If there is no feedback, why might that be so and what can you do about it?
• Devise a Plan : Have you seen this problem, or something like it, before? If you haven’t seen this problem before, can you restate it in terms you are familiar with? Can you break the problem down into smaller problems that are familiar and accessible?
• Execute the Plan
• Examine the Solution : What is the solution? Explain it. Can it be modified? If so, what could be improved, if anything? Could we use this solution for other problems?

Problem solving is an iterative activity for developers.

• First, we implement a solution
• Then, we troubleshoot the implementation

We don’t always get it right the first time, which is part of the iterative process and why it’s important to prioritize problem solving as a fundamental skill. First, we attempt to solve a given problem; then, we attempt to solve the problem(s) created by our solution. We as developers know we can always take our solutions another step further with refactoring. The processes of iterative development and refactoring are metacognitive. We are thinking about thinking. When our first attempt at a solution throws an error (or is inelegant), we are forced to confront and evaluate the limits of our intuitions.

One does not expect anything to work at the first try. One does not judge by standards like ‘right—you get a good grade’ and ‘wrong—you get a bad grade’. Rather one asks the question: ‘How can I fix it?’ and to fix it one has first to understand what happened in its own terms.

-Seymour Papert

In Mindstorms , Papert introduces the concept of microworlds. In programming, a microworld is a self-contained environment in which the learner can model and test assumptions, or intuitions. Each activity, each homework assignment, each project is a microworld. The boundaries of the microworld are simultaneously defined by the language and by the learner’s approach to the language. When programming, we will have intuitions about how it should work but we may be presented with evidence that it does not work (bugs!). Papert sees the computer as helping learners confront their intuitions in two ways:

The computer allows, or obliges, the [learner] to externalize intuitive expectations. When the intuition is translated into a program it becomes more obtrusive and more accessible to reflection.

Computational ideas can be taken up as materials for the work of remodeling intuitive knowledge.

The key to long-term success in programming is in this two-fold process of reflection and remodeling, or, learning how to think about thinking . Ultimately, what each of us needs is a better understanding of ourselves. Why did you think this approach would or would not work? Why do you think it does or doesn’t? What does this situation reveal to you about your assumptions and intuitions? Your biases? Bugs are “an intrinsic part of the learning process”, not something to be avoided. It is through debugging that we learn the most about ourselves.

Reflect and Remodel

The key technique is asking yourself why you made a particular mistake, rather than just fixing the mistake and moving on.

If the choice is ‘ Program or Be Programmed ’, the answer is obviously the former, not because of some economic inevitability, but because the primary skill one acquires through programming is problem-solving. A problem-solving mindset not only equips one with the ability to think critically about a given problem, but to think critically about oneself.

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Programming Tutorial | Introduction, Basic Concepts, Getting started, Problems

This comprehensive guide of Programming Tutorial or Coding Tutorial provides an introduction to programming, covering basic concepts, setting up your development environment, and common beginner problems. Learn about variables, data types, control flow statements, functions, and how to write your first code in various languages. Explore resources and tips to help you to begin your programming journey. We designed this Programming Tutorial or Coding Tutorial to empower beginners and equip them with the knowledge and resources they will need to get started with programming.

Programming Tutorial

1. What is Programming?

Programming , also known as coding , is the process of creating a set of instructions that tell a computer how to perform a specific task. These instructions, called programs, are written in a language that the computer can understand and execute.

Table of Content

• What is Programming?
• Getting Started with Programming
• Common Programming Mistakes and How to Avoid Them
• Basic Programming EssentialsA Beginner’s Guide to Programming Fundamentals
• Advanced Programming Concepts
• Writing Your First Code
• Top 20 Programs to get started with Coding/Programming
• Next Steps after learning basic Coding/Programming
• Resources and Further Learning
• Frequently Asked Questions (FAQs) on Programming Tutorial

Think of programming as giving commands to a robot. You tell the robot what to do, step-by-step, and it follows your instructions precisely. Similarly, you tell the computer what to do through code, and it performs those tasks as instructed.

The purpose of programming is to solve problems and automate tasks. By creating programs, we can instruct computers to perform a wide range of activities, from simple calculations to complex tasks like managing databases and designing video games.

A. How Programming Works:

Programming involves several key steps:

• Problem definition: Clearly define the problem you want to solve and what you want the program to achieve.
• Algorithm design: Develop a step-by-step procedure for solving the problem.
• Coding: Translate the algorithm into a programming language using a text editor or integrated development environment (IDE).
• Testing and debugging: Run the program and identify and fix any errors.
• Deployment: Share the program with others or use it for your own purposes.

B. Benefits of Learning to Code:

Learning to code offers numerous benefits, both personal and professional:

• Develop critical thinking and problem-solving skills: Programming encourages logical thinking, problem decomposition, and finding creative solutions.
• Boost your creativity and innovation: Coding empowers you to build your own tools and applications, turning ideas into reality.
• Increase your employability: The demand for skilled programmers is high and growing across various industries.
• Improve your communication and collaboration skills: Working with code often requires collaboration and clear communication.
• Gain a deeper understanding of technology: Learning to code gives you a better understanding of how computers work and how they are used in the world around you.
• Build self-confidence and motivation: Successfully completing programming projects can boost your confidence and motivate you to learn new things.

Whether you’re interested in pursuing a career in technology or simply want to expand your knowledge and skills, learning to code is a valuable investment in your future.

2. Getting Started with Programming Tutorial

A. choosing your first language.

Assess Resource Availability:

• Free Online Resources: Platforms like Geeksforgeeks, Coursera, edX, and Udemy offer structured learning paths for various languages.
• Paid Online Courses: Platforms like Geeksforgeeks, Coursera, edX, and Udemy offer structured learning paths for various languages.
• Books and eBooks: Numerous beginner-friendly books and ebooks are available for most popular languages.
• Community Support: Look for active online forums, communities, and Stack Overflow for troubleshooting and questions.

B. Which Programming Language should you choose as your First Language?

Here’s a breakdown of popular beginner-friendly languages with their Strengths and Weaknesses:

C. Setting Up Your Development Environment

Choose a Text Editor or IDE :

• Text Editors: Sublime Text, Atom, Notepad++ (lightweight, good for beginners)
• Offline IDEs: Visual Studio Code, PyCharm, IntelliJ IDEA (feature-rich, recommended for larger projects)
• Online IDEs: GeeksforGeeks IDE

Install a Compiler or Interpreter:

• Compilers: Convert code to machine language (C++, Java)
• I nterpreters: Execute code line by line (Python, JavaScript)

Download Additional Software (if needed):

• Web browsers (Chromium, Firefox) for web development
• Android Studio or Xcode for mobile app development
• Game engines (Unity, Unreal Engine) for game development

Test Your Environment:

• Write a simple program (e.g., print “Hello, world!”)
• Run the program and verify the output
• Ensure everything is set up correctly
• Start with a simple editor like Sublime Text for code basics.
• Use an IDE like Visual Studio Code for larger projects with advanced features.
• Join online communities or forums for help with setup issues.

3. Common Programming Mistakes and How to Avoid Them

• Syntax errors: Typographical errors or incorrect grammar in your code.
• Use syntax highlighting in your editor or IDE.
• Logical errors: Errors in the logic of your program, causing it to produce the wrong results.
• Carefully review your code and logic.
• Test your program thoroughly with different inputs.
• Use debugging tools to identify and fix issues.
• Runtime errors: Errors that occur during program execution due to unforeseen circumstances.
• Seek help from online communities or forums for specific errors.
• Start with simple programs and gradually increase complexity.
• Write clean and well-formatted code for better readability.
• Use comments to explain your code and logic.
• Practice regularly and don’t be afraid to experiment.
• Seek help from online communities or mentors when stuck.

4. Basic Programming Essentials – A Beginner’s Guide to Programming Fundamentals:

This section delves deeper into fundamental programming concepts that form the building blocks of any program.

A. Variables and Data Types:

Understanding Variable Declaration and Usage:

• Variables are containers that hold data and can be assigned different values during program execution.
• To declare a variable, you specify its name and data type, followed by an optional assignment statement.
• Example: age = 25 (declares a variable named age of type integer and assigns it the value 25).
• Variables can be reassigned new values throughout the program.

Exploring Different Data Types:

• Integers: Whole numbers without decimal points (e.g., 1, 2, -3).
• Floats: Decimal numbers with a fractional part (e.g., 3.14, 10.5).
• Booleans: True or False values used for conditions.
• Characters: Single letters or symbols (‘a’, ‘$’, ‘#’).
• Strings: Sequences of characters (“Hello, world!”).
• Other data types: Arrays, lists, dictionaries, etc. (depending on the language).

Operations with Different Data Types:

Each data type has supported operations.

• Arithmetic operators (+, -, *, /) work with integers and floats.
• Comparison operators (==, !=, >, <, >=, <=) compare values.
• Logical operators (&&, ||, !) combine conditions.
• Concatenation (+) joins strings.
• Operations with incompatible data types may lead to errors.

B. Operators and Expressions:

Arithmetic Operators:

• Perform basic mathematical calculations (+, -, *, /, %, **, //).
• % (modulo) returns the remainder after division.
• ** (power) raises a number to a certain power.
• // (floor division) discards the fractional part of the result.

Comparison Operators:

• Evaluate conditions and return True or False.
• == (equal), != (not equal), > (greater than), < (less than), >= (greater than or equal), <= (less than or equal).

Logical Operators: Combine conditions and produce True or False.

• && (and): both conditions must be True.
• || (or): at least one condition must be True.
• ! (not): reverses the truth value of a condition.

Building Expressions:

• Combine variables, operators, and constants to form expressions.
• Expressions evaluate to a single value. Example: result = age + 10 * 2 (calculates the sum of age and 20).

C. Control Flow Statements:

Conditional Statements: Control the flow of execution based on conditions.

• if-else: Executes one block of code if the condition is True and another if it’s False.
• switch-case: Executes different code blocks depending on the value of a variable.

Looping Statements: Repeat a block of code multiple times.

• for: Executes a block a specific number of times.
• while: Executes a block while a condition is True.
• do-while: Executes a block at least once and then repeats while a condition is True.

Nested Loops and Conditional Statements:

• Can be combined to create complex control flow structures.
• Inner loops run inside outer loops, allowing for nested logic.

D. Functions:

Defining and Calling Functions:

• Blocks of code that perform a specific task.
• Defined with a function name, parameters (optional), and a code block.
• Called throughout the program to execute the defined functionality.

Passing Arguments to Functions:

• Values passed to functions for processing.

Returning Values from Functions:

• Functions can return a value after execution.
• Useful for collecting results.
• A function calling itself with a modified input.
• Useful for solving problems that involve repetitive tasks with smaller inputs.

These topics provide a solid foundation for understanding programming fundamentals. Remember to practice writing code and experiment with different concepts to solidify your learning.

5. Advanced Programming Concepts

This section explores more advanced programming concepts that build upon the foundational knowledge covered earlier.

A. Object-Oriented Programming (OOP)

OOP is a programming paradigm that emphasizes the use of objects to represent real-world entities and their relationships.

1. Classes and Objects:

• Classes: Define the blueprint for objects, specifying their properties (attributes) and behaviors (methods).
• Objects: Instances of a class, with their own set of properties and methods.

2. Inheritance and Polymorphism:

• Inheritance: Allows creating new classes that inherit properties and methods from existing classes (superclasses).
• Polymorphism: Enables objects to respond differently to the same message depending on their type.

3. Encapsulation and Abstraction:

• Encapsulation: Encloses an object’s internal state and methods, hiding implementation details and exposing only a public interface.
• Abstraction: Focuses on the essential features and functionalities of an object, ignoring unnecessary details.

B. Concurrency and Parallelism

Concurrency and parallelism are crucial for improving program efficiency and responsiveness.

1. Multithreading and Multiprocessing:

• Multithreading: Allows multiple threads of execution within a single process, enabling concurrent tasks.
• Multiprocessing: Utilizes multiple processors to run different processes simultaneously, achieving true parallelism.

2. Synchronization and Concurrency Control:

Mechanisms to ensure data consistency and prevent conflicts when multiple threads or processes access shared resources.

6. Writing Your First Code

Here is your first code in different languages. These programs all achieve the same goal: printing “ Hello, world! ” to the console. However, they use different syntax and conventions specific to each language.

Printing “Hello world” in C++:

Explanation of above C++ code:

• #include: This keyword includes the <iostream> library, which provides functions for input and output.
• int main(): This defines the main function, which is the entry point of the program.
• std::cout <<: This keyword prints the following expression to the console.
• “Hello, world!” This is the string that is printed to the console.
• std::endl: This keyword inserts a newline character after the printed string.
• return 0; This statement exits the program and returns a success code (0).

Printing “Hello world” in Java:

Explanation of above Java code:

• public class HelloWorld: This keyword defines a public class named HelloWorld .
• public static void main(String[] args): This declares the main function, which is the entry point of the program.
• System.out.println(“Hello, world!”); This statement prints the string “ Hello, world! ” to the console.

Printing “Hello world” in Python:

Explanation of above Python code:

• print: This keyword prints the following argument to the console.

Printing “Hello world” in Javascript:

Explanation of above Javascript code:

• console.log: This object’s method prints the following argument to the console.

Printing “Hello world” in PHP:

Explanation of above PHP code:

• <?php: This tag initiates a PHP code block.
• echo: This keyword prints the following expression to the console.
• ?>: This tag ends the PHP code block.

7. Top 20 Programs to get started with Coding/Programming Tutorial:

Here are the list of some basic problem, these problems cover various fundamental programming concepts. Solving them will help you improve your coding skills and understanding of programming fundamentals.

8. Next Steps after learning basic Coding/Programming Tutorial:

Congratulations on taking the first step into the exciting world of programming! You’ve learned the foundational concepts and are ready to explore more. Here’s a comprehensive guide to help you navigate your next steps:

A. Deepen your understanding of Basic Programming Concepts:

• Practice regularly: Implement what you learn through practice problems and coding exercises.
• Solve code challenges: Platforms like GeeksforGeeks, HackerRank, LeetCode, and Codewars offer challenges to improve your problem-solving skills and coding speed.

B. Learn advanced concepts:

• Data structures: Learn about arrays, linked lists, stacks, queues, trees, and graphs for efficient data organization.
• Algorithms: Explore algorithms for searching, sorting, dynamic programming, and graph traversal.
• Databases: Learn SQL and NoSQL databases for data storage and retrieval.
• Version control: Use Git and GitHub for code versioning and collaboration.

C. Choose a focus area:

• Web development: Learn HTML, CSS, and JavaScript to build interactive web pages and applications.
• Mobile app development: Choose frameworks like Flutter (Dart) or React Native (JavaScript) to build cross-platform apps.
• Data science and machine learning: Explore Python libraries like NumPy, pandas, and scikit-learn to analyze data and build machine learning models.
• Game development: Learn game engines like Unity (C#) or Unreal Engine (C++) to create engaging games.
• Desktop app development: Explore frameworks like PyQt (Python) or C# to build desktop applications.
• Other areas: Explore other areas like robotics, embedded systems, cybersecurity, or blockchain development based on your interests.

D. Build projects:

• Start with small projects: Begin with simple projects to apply your knowledge and gain confidence.
• Gradually increase complexity: As you progress, tackle more challenging projects that push your boundaries.
• Contribute to open-source projects: Contributing to open-source projects is a great way to learn from experienced developers and gain valuable experience.
• Showcase your work: Create a portfolio website or blog to showcase your skills and projects to potential employers or clients.

9. Resources and Further Learning

A. Online Courses and Tutorials:

• Interactive platforms: GeeksforGeeks, Codecademy, Coursera, edX, Khan Academy
• Video tutorials: GeeksforGeeks, YouTube channels like FreeCodeCamp, The Coding Train, CS50’s Introduction to Computer Science
• Language-specific tutorials: GeeksforGeeks, Official documentation websites, blogs, and community-driven resources

B. Books and eBooks:

• Beginner-friendly books: “Python Crash Course” by Eric Matthes, “Head First Programming” by David Griffiths
• A dvanced topics: “Clean Code” by Robert C. Martin, “The Pragmatic Programmer” by Andrew Hunt and David Thomas
• Free ebooks: Many free programming ebooks are available online, such as those on Project Gutenberg

C. Programming Communities and Forums:

• Stack Overflow: Q&A forum for programming questions
• GitHub: Open-source platform for hosting and collaborating on code projects
• Reddit communities: r/learnprogramming, r/python, r/webdev
• Discord servers: Many languages have dedicated Discord servers for discussions and support

D. Tips for Staying Motivated and Learning Effectively:

• Set realistic goals and deadlines.
• Start small and gradually increase complexity.
• Practice regularly and code consistently.
• Find a learning buddy or group for accountability.
• Participate in online communities and forums.
• Take breaks and avoid burnout.
• Most importantly, have fun and enjoy the process

10. Frequently Asked Questions (FAQs) on Programming Tutorial:

Question 1: how to learn programming without tutorial.

Answer: Learning programming without tutorials involves a self-directed approach. Start by understanding fundamental concepts, practicing regularly, and working on small projects. Utilize books, documentation, and online resources for reference.

Question 2: How to learn coding tutorial?

Answer: Learning coding through tutorials involves choosing a programming language, finding online tutorials or courses, and following them step by step. Practice coding alongside the tutorial examples and apply the concepts to real-world projects for a hands-on learning experience.

Question 3: What are 3 important things to know about programming?

Answer: Problem Solving: Programming is fundamentally about solving problems. Logic and Algorithms: Understanding logical thinking and creating efficient algorithms is crucial. Practice: Regular practice and hands-on coding improve skills and understanding.

Question 4: How many days do I need to learn programming?

Answer: The time to learn programming varies based on factors like prior experience, the complexity of the language, and the depth of knowledge desired. Learning the basics can take weeks, but mastery requires continuous practice over months.

Question 5: Can tutorials help coding?

Answer: Yes, tutorials are valuable resources for learning coding. They provide structured guidance, examples, and explanations, making it easier to understand and apply Programming Tutorial concepts.

Question 6: How do you use tutorials effectively?

Answer: Use tutorials effectively by following these steps: Set clear learning goals. Work on hands-on exercises and projects. Seek additional resources for deeper understanding. Regularly review and practice concepts learned.

Question 7: Can coding be done on a phone?

Answer: Yes, coding can be done on a phone using coding apps or online platforms that provide mobile-friendly coding environments. However, a computer is generally more practical for extensive coding tasks.

Question 8: Can I learn coding on GeeksforGeeks?

Answer: Yes, GeeksforGeeks is a popular platform for learning coding. Many Tutorials, Courses are provided you to learn various programming languages and concepts.

Question 9: Can we do coding on a laptop?

Answer: Yes, coding can be done on a laptop. Laptops are common tools for coding as they provide a portable and versatile environment for writing, testing, and running code.

Question 10: What is the difference between coding and programming?

Answer: The terms are often used interchangeably, but coding is typically seen as the act of writing code, while programming involves a broader process that includes problem-solving, designing algorithms, and implementing solutions. Programming encompasses coding as one of its stages.

This comprehensive programming tutorial has covered the fundamentals you need to start coding. Stay updated with emerging technologies and keep practicing to achieve your goals. Remember, everyone starts as a beginner. With dedication, you can unlock the world of programming!

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The Importance of Programming in Today’s Digital World

Programming has become an essential skill in today’s digital world. From smartphones and websites to artificial intelligence and self-driving cars, programming is at the core of innovation and technological advancement. In this article, we will explore the importance of programming and why it is worth considering as a valuable skill to possess.

Enhances Problem-Solving Abilities

Programming encourages the development of logical thinking and problem-solving skills. When writing code, programmers often encounter complex challenges that require careful analysis and attention to detail. By breaking down a problem into smaller, manageable components, programmers learn to think critically and devise creative solutions. These problem-solving abilities can be applied not only to coding but also to various aspects of life, including decision-making and troubleshooting.

Unleashes Creativity

Contrary to popular belief, programming is not just about mathematical equations and algorithms. In fact, coding provides a platform for creativity and self-expression. Programmers have the freedom to design and build their own software, games, or applications from scratch. Whether it’s developing a visually stunning website or creating an interactive mobile app, programming allows individuals to bring their unique ideas to life.

Fuels Innovation

Some of the most revolutionary developments in recent years have emerged from the realm of programming. From social media platforms to e-commerce websites, programming plays a pivotal role in shaping our digital landscape. By learning how to code, individuals can actively contribute to the creation of innovative technologies that improve our lives. Moreover, programming exposes individuals to advanced concepts such as machine learning and artificial intelligence, enabling them to actively participate in the frontier of technological advancement.

Opens Career Opportunities

The demand for skilled programmers is constantly on the rise. As technology continues to evolve, businesses require professionals who can develop and maintain their digital ecosystem. By learning programming languages such as Python, Java, or JavaScript, individuals can unlock a wide range of career opportunities in software development, web development, data analysis, and more. Additionally, programming skills are highly transferable, allowing individuals to work remotely or freelance while enjoying a flexible work-life balance.

Fosters Digital Literacy

In an era where technology permeates every aspect of our lives, digital literacy has become a necessity. Understanding the fundamentals of programming empowers individuals to navigate our increasingly digital world with confidence. It enables them to adapt to new technologies, make informed decisions about digital security, and fully leverage the potential of digital tools available to them.

Programming is no longer confined to the realm of IT professionals or computer science graduates. It has become an essential skill for anyone aspiring to thrive in today’s digital world. The ability to code not only enhances problem-solving abilities and fuels innovation but also opens doors to exciting career prospects. Moreover, it fosters digital literacy and empowers individuals to actively participate in shaping the future. So, why not explore the world of programming and unlock your full potential in this digital age?

What is problem solving and why is it important

By Wayne Stottler , Kepner-Tregoe

• Problem Solving & Decision Making Over time, developing and refining problem solving skills provides the ability to solve increasingly complex problems Learn More

For over 60 years, Kepner-Tregoe has been helping companies across industries and geographies to develop and mature their problem-solving capabilities through KT’s industry leading approach to training and the implementation of best practice processes. Considering that problem solving is a part of almost every person’s daily life (both at home and in the workplace), it is surprising how often we are asked to explain what problem solving is and why it is important.

Problem solving is at the core of human evolution. It is the methods we use to understand what is happening in our environment, identify things we want to change and then figure out the things that need to be done to create the desired outcome. Problem solving is the source of all new inventions, social and cultural evolution, and the basis for market based economies. It is the basis for continuous improvement, communication and learning.

If this problem-solving thing is so important to daily life, what is it?

Problem-solving is the process of observing what is going on in your environment; identifying things that could be changed or improved; diagnosing why the current state is the way it is and the factors and forces that influence it; developing approaches and alternatives to influence change; making decisions about which alternative to select; taking action to implement the changes; and observing impact of those actions in the environment.

Each step in the problem-solving process employs skills and methods that contribute to the overall effectiveness of influencing change and determine the level of problem complexity that can be addressed. Humans learn how to solve simple problems from a very early age (learning to eat, make coordinated movements and communicate) – and as a person goes through life problem-solving skills are refined, matured and become more sophisticated (enabling them to solve more difficult problems).

Problem-solving is important both to individuals and organizations because it enables us to exert control over our environment.

Fixing things that are broken

Some things wear out and break over time, others are flawed from day-1. Personal and business environments are full of things, activities, interactions and processes that are broken or not operating in the way they are desired to work. Problem-solving gives us a mechanism for identifying these things, figuring out why they are broken and determining a course of action to fix them.

Addressing risk

Humans have learned to identify trends and developed an awareness of cause-and-effect relationships in their environment. These skills not only enable us to fix things when they break but also anticipate what may happen in the future (based on past-experience and current events). Problem-solving can be applied to the anticipated future events and used to enable action in the present to influence the likelihood of the event occurring and/or alter the impact if the event does occur.

Improving performance

Individuals and organizations do not exist in isolation in the environment. There is a complex and ever-changing web of relationships that exist and as a result, the actions of one person will often have either a direct impact on others or an indirect impact by changing the environment dynamics. These interdependencies enable humans to work together to solve more complex problems but they also create a force that requires everyone to continuously improve performance to adapt to improvements by others. Problem-solving helps us understand relationships and implement the changes and improvements needed to compete and survive in a continually changing environment.

Seizing opportunity

Problem solving isn’t just about responding to (and fixing) the environment that exists today. It is also about innovating, creating new things and changing the environment to be more desirable. Problem-solving enables us to identify and exploit opportunities in the environment and exert (some level of) control over the future.

Problem solving skills and the problem-solving process are a critical part of daily life both as individuals and organizations. Developing and refining these skills through training, practice and learning can provide the ability to solve problems more effectively and over time address problems with a greater degree of complexity and difficulty. View KT’s Problem Solving workshop known to be the gold standard for over 60 years.

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What is Programming?

Why is computer programming important, what are the benefits of computer programming, how can computer programming or coding help the world, jobs after learning computer programming.

In today’s society, knowing how to computer program is one of the most valuable skills somebody can possess. It is an essential tool that enables us to communicate with computers and complete tasks. It has a wide range of uses, from managing businesses to creating new products. The importance of computer programming cannot be understated. It helps us solve problems and carry out tasks more efficiently. It also allows us to automate processes and create new ways of doing things. Computer programming is a highly sought-after skill in an increasingly technological world.

If you’re wondering why is programming important, then keep reading. In this article, we will discuss the importance of computer programming and why it is an important skill to have.

First, it is important to define the term “programming”. According to Wikipedia, “Programming is the act of writing or debugging a computer program.” In other terms, it is the procedure for developing and running a program.

 Programming is a process of designing and writing computer programs that make the workings of a computer more efficient. It is a form of communication that uses symbols to represent instructions for making a machine do what you want.

Programming enables people to solve practical problems by breaking them down into a series of logical steps, known as algorithms or programs. Application developers can use any number of programming languages to write applications for specific kinds of computers, like supercomputers, laptops, and smartphones.

High-level programming languages (like C++ or Java) create human-readable programs. A program’s machine code is written in a language that’s machine-readable (like C or Python) and is only understandable by computers.

You can categorize software into a lot of subcategories and use it for a lot of things.

Many are created for particular uses in fields like medicine, engineering, finance, or education. Some examples of popular software applications include word processors, computer games, web browsers, and spreadsheets.

Computer programming is one of the most important aspects of modern life. It allows us to interact with computers in ways that were not possible before. It has enabled us to conduct research, design new products, and services, manage our finances, communicate with others around the World, and much more.

Computers and the internet have completely changed the way we live our lives and interact with the world around us. It allows us to connect with people on the other side of the globe in an instant. Programming has changed the way we shop, travel, learn, and work. They are an essential part of our everyday lives. Without computers and the internet, our lives would be very different. There would be no Facebook or YouTube. There would be no online banking or e-commerce. And it would not be possible to shop online for thousands of different products and have them delivered to your home with a single click of the mouse.

Over the past few decades, computer programming has played an important role in the development of the modern computer and the information age that we live in today. It has allowed us to create new computer software and systems that make many aspects of our lives easier.

Computer Programming allows us to create new internet-based applications and services that make it possible for us to communicate and collaborate with one another like never before.

The benefits of computer programming are not limited to the business world. They also have a significant impact on education, healthcare, entertainment, and other areas of life as well. Computer programming plays an important role in our daily lives. Without it, our lives would be completely different. Besides helping develop new technologies, it also makes a lot of everyday things easier.

Programming is a fascinating and versatile field you can use for so many different things. Here are just a few of the benefits:

• Computer programming can be used to create innovative and functional software. Computer programmers can use their creativity to design software that will be useful to people, or that will improve the way that people work. For example, a computer programmer might design a program that analyzes data from medical tests to determine the presence of a particular disease. The program could be used to help doctors diagnose the disease more easily and accurately.
• Computers can also be programmed to perform specific tasks using mathematical algorithms and logic. Computer programmers can create programs that use these algorithms to carry out tasks such as sorting data or calculating the results of complex equations.
• It can also be used to create websites, games, and other digital content. In this way, computer programs make it possible for people to access a wide range of entertainment and information online. In addition to creating new content, computer programmers can also help improve existing software and applications. They can add new features and options to existing programs to improve the usability and quality of these programs. For example, a programmer could update an existing gaming app to make it easier to use on a smartphone.

These are just a few instances of how computer programming may be utilized to tackle a wide range of real-world issues. There are numerous other ways in which computer programs might benefit society as a whole.

Computer programmers can help to develop new methods and technologies to improve healthcare and research. They can also create fresh approaches to lower energy usage and increase energy efficiency. As you can see, computer programming offers a diverse range of benefits that can help to enhance our everyday lives in numerous ways.

Computer programming and coding have the potential to positively impact many aspects of our world. By using them, we will be able to create tools that will simplify our lives, solve complex problems, and make our lives easier. In fact, computer programmers and coders are responsible for countless innovations and advancements across many industries!

Improve Healthcare

It can improve healthcare through the use of technology. Coding skills can help healthcare organizations develop apps and other tools that can help manage medical records and improve patient care.

For example, the use of codes can help doctors and healthcare providers better understand how to treat their patients by tracking and analyzing patient data.

Patients can also manage their health more easily with smartphone apps developed with coding skills.

Positive impact on the environment

Programming creates apps and other technology that can aid in reducing the environmental effect of specific activities.

Apps that educate users about local public transportation alternatives and alternate modes of transportation can assist users in reducing their use of fossil fuels.

Users can create apps to reduce waste through recycling programs and promote sustainable living by leveraging their programming skills.

Discover the environment we live in

Programming helps us learn about the world around us. It pertains to the development of apps that allow users to travel around the world and discover intriguing facts about a variety of subjects.

By comparing images of different plants and animals to a database of pictures of similar species, developers can create apps that let users recognize various types of plants and animals.

It is also possible to create apps that let users explore historical sites and discover the past of various towns all over the world.

Encourages inclusion and diversity

They can promote diversity and inclusion. It is possible to create apps that support diversity in our society using programming abilities.

By encouraging users to share their own encounters with persons from minority groups or those with impairments. These apps help in encouraging inclusivity.

Mobile apps facilitate communication between people from different cultural backgrounds and worldviews and help people learn about other cultures.

Encourage economic growth

Programming can help fuel our economy. Coding abilities may be utilized to create apps that assist people in finding work. These apps will assist job seekers in discovering employment possibilities across a variety of sectors, including tech, healthcare, media, entertainment, and education.

Programming can also help employers manage their recruitment process more effectively by making it easier for them to find and hire qualified candidates for open positions.

After learning computer programming, many students want to find jobs that use this skill set. Here are some of the most common jobs after learning computer programming:

• Computer Programmer – In today’s digital world, computer skills are a must if you want to get a job. Programming experience is a plus. As a computer programmer, you can work in a variety of industries including banking, finance, healthcare, and retail.
• Software Development Engineer – A software development engineer works in a technical environment to design and develop computer software for a variety of platforms. Requirements vary depending on the employer, but employers generally look for a degree in computer science or software engineering.
• Cloud Architect – The cloud architect helps design and create cloud-based solutions for clients. This person should be well-versed in cloud computing concepts and have strong problem-solving abilities. Responsibilities may include analyzing requirements, creating cloud architectures, and designing solutions to meet client requirements.

Programming is important for a variety of reasons. It helps us automate tasks, create new technologies, and develop more efficient systems. With the ever-growing importance of technology in our world, learning to program is becoming more and more essential. Thanks for reading!

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