How can you develop your problem-solving skills in programming through real-world experience?

Draw a scenario identifying the problem outside coding and programming For example you were asked to write a code demonstrating binary search in array so first thing you think he wants me to look at list of sorted numbers and he wants me to find a specific number in this list so first I must have a middle number to start at and then either look at the right or left side of this number depending on the number I want to find so I can shift the middle number to be another number Here I didn't even think of arrays or pointers or how am I even going to solve it but as soon as you reach the logic in your mind the coding becomes less harder to write

My number one step is to draw a diagram. Try to visually represent the problem at hand: - Computations and data — what does it look like, what are your dimensions. - Input and output — decide what the end goal is and what parameters you can change; what your program should return/if at all. Add this to your diagram!. - What steps need to be taken — add these to a flowchart; start broad, don't go into too much detail yet. - How does each step relate to the previous and subsequent operations — make note of your in/outputs. Next, ask who/what is this for? And, are there any design constraints? This will affect your choice of platform, but also how you collaborate — you need to identify how to communicate your work.

Here is my opinion. - Learn about the Problem. - Break the problem into smaller parts. - Don't get exhausted, taking break is fine, no one can climb the mountain in one go :D - Problem solved! it does not mean always get the desired outcome but yes things don't block your way once you understand them.

Users expressed dissatisfaction with poor loading times when a simple e-commerce website was built. Examining the code in detail to determine the issue led to the discovery that the huge product images were the cause. I learned how important it is to identify issues precisely through this practical problem-solving exercise.

Begin problem-solving by clearly defining the problem—understand requirements, constraints, expected outcomes, and potential pitfalls. Employ techniques like questioning, breaking down, drawing diagrams, or pseudocode. This avoids wasting time and resources on irrelevant or incorrect solutions.

Sometimes it's cool to dive way deeper than needed. I've dealt with tons of regex at work. At first, nailing the right regex was a struggle. Even checking StackOverflow didn't always yield precisely what I was looking for. I got sick of wasting 30 minutes on each, so I dedicated a week to thoroughly learning how to write regex patterns, and since then, I've never spent more than 5-10 minutes on any I've done thereafter. I've tackled quite a few because my colleagues specifically reached out to me when they're stuck on tricky ones, like email validation, for example.

Look for similar problems that others have solved. Study their approaches, algorithms, and methodologies. Analyze both successful and unsuccessful attempts. Dive into documentation, programming language guides, online courses, forums (like Stack Overflow), blogs, or books related to the problem domain.

Once the problem is identified, invest time in research. Explore existing solutions, relevant documentation, and community forums. Acquiring knowledge about similar problems and their resolutions broadens your understanding and equips you with diverse approaches to problem-solving.

In my experience, research should begin before you were even given the problem at hand. That is, the best way to solve problems is to always be learning — the number of times I have been able to solve a specific problem due to accumulated general knowledge not trivial. Even for problems you have solved 100s of times before, with just a little extra digging, you can stumble across new and effective ways to do things, all the while adding an array of techniques to your workflow. On this note, it is very important to keep up to date; countless times, I have seen people stuck using inefficient, outdated techniques, when there are so many new ways to develop effectively — keep learning new ways to do the same thing!

Unexpected flaws were produced by a complicated algorithm during collaborative coding. Testing became essential, and I learned how important it is to create thorough test cases. This experience strengthened the practice of taking edge cases into account while implementing code and increased code reliability.

Based on your understanding and research, start implementing a solution. Break it into smaller, manageable parts and tackle each part iteratively. Develop test cases that cover various scenarios and edge cases. Apply different testing methods such as unit testing, integration testing, and regression testing to ensure your solution is robust.

Profiling. I wish I had learnt this invaluable technique sooner. Too often you may wonder why your code is running so slow, and spend hours on stack overflow trying to find an answer. Profiling tells your which function/processes are eating into your CPU & memory. This is the key starting point to learning better code; from here you will gain a deeper understanding of how your program actually work behind the scenes: how often you create new arrays, where they are being stored, how your program is compiling etc... I also highly recommend documenting: if you are struggling to explain what your program does and how it works, then this is a crucial gateway to self-reflection — it forces you to reevaluate the structure/complexity of your code!

Review your code and solution critically. Identify areas where improvements can be made in terms of performance, readability, or efficiency. Modify your code to enhance its quality without altering its behavior. This might involve improving variable names, restructuring code, or optimizing algorithms.

By taking part in hackathons and coding projects, I was able to put my theoretical knowledge to use. Interacting with varied developers promoted a collaborative perspective and exposed one to a range of problem-solving techniques.

This goes hand-in-hand with research and learning; in fact they might be equivalent. The best way to LEARN, is to DO. The more time you spend problem solving, and the larger the variety of problem you work on, the better. It can be hard to understand, for example, what is actually means to write good, professional, understandable code until you actually work with others — there are some areas of knowledge/experience which aren't easily/clearly documented in the guidebooks or online forums — some things are best learnt from your peers; the feedback you get will be invaluable. Most importantly: keep an open mind — do not let your biases get in the way of constructive criticism; surround yourself with people who give honest feedback.

Engage in real-world projects either through internships, freelancing, or personal initiatives. Work on tasks that challenge you and offer practical experience. Join coding communities, contribute to open-source projects, or participate in hackathons. Collaborate with others to tackle diverse problems and learn from different perspectives.

Using LinkedIn to network offered doors to mentorship. Talking with seasoned engineers gave me insights into best practices in the field. I also gained a deeper awareness of the larger programming ecosystem by going to tech meetups. The integration of these real-world experiences greatly improved my ability to solve problems in programming.

Stay curious and cultivate a growth mindset. Actively seek feedback from peers and mentors, and embrace the learning opportunities presented by both successes and failures. Regularly participate in coding challenges, hackathons, and collaborative coding sessions to further sharpen your problem-solving skills.