7 Tips on How to Approach and Solve Coding Problems Successfully

Proficiency in software development is often associated with the ability to write complex codes in a short span of time. However, in practice, the field is as much about critical analysis and communication as it is about tackling coding challenges quickly and efficiently. At its core, software programming essentially means to solve problems. It teaches you to think analytically and determine the best possible solution to a problem — something that is common among all successful software developers. 

So, if you hope to excel at writing code and land the job of your dreams, you should begin with building your problem-solving abilities. In this article, we will provide you with 7 proven tips to approach problems so you get better at coding. So, let’s get started with the first one!

You should be well-versed with the underlying logic of algorithms so as to determine optimal solutions to coding problems. So, begin with brushing up on basic data structures and algorithms, and developing in-depth understanding of core conceits. It is recommended that you take it slow; increase the difficulty level of your learning and coding gradually. In any case, do not directly jump onto something advanced without learning the basics. 

You should also ensure that you don't get comfortable with executing codes using just one approach. The idea is to familiarize yourself with different problem-solving techniques to build your coding skills. One way to do this is to solve a variety of coding problems on challenging coding platforms like HackerRank, HackerEarth, Codewars, GitHub, to name a few. This will force you to be flexible, and employ the best possible framework for every problem.

It helps if you break the large and complex problem into sections and address them part by part. This will help you write simple and efficient codes devoid of any unnecessary complexities. 

Here's what you can do:

• Create a flow chart illustrating the problem.
• Break it into subproblems or smaller sections.
• Solve each section by creating independent functions.
• Arrange the functions in the order you need, thereby merging them all for the final solution. 
• In case of errors, you can debug the code and search for an alternate approach. 

You can draw up the pseudo code and run it logically before replacing it with the original code. A pseudocode provides clarity on the requirements and functioning of the code, and thus makes writing the actual code easier. So, don't make the mistake of skipping this step. 

While there are a ton of programming algorithms and data structures to help you write codes, you should be able to choose the right software for optimised coding; hardware can not compensate for inefficiencies that arise due to incorrect algorithms and data structures. 

This is where time and space complexity, and stability come into the picture. For instance, the selection sort may not be the recommended for larger lists, it is highly efficient to sort smaller lists. Similarly, binary search is considered to be the quickest and most efficient search algorithm; however, linear search or breadth-first search also have their distinct advantages. 

So, given a problem, ask yourself, which sorting method is best suited for your input? Is it possible to eliminate nested loops? Does this search method provide a performance advantage? 

Examine the solution code thoroughly while simultaneously paying close attention to the time and space complexity. Determine if arrays, strings, binary trees, sorting, or loops are best suited to attain your goal. 

Run your code through edge cases by feeding empty or unacceptable inputs so you become aware of boundary conditions. LeetCode is an excellent platform when looking for coding problems to solve optimally. 

Simply finding a solution to a coding problem should not be your primary goal; you should actively revisit your old codes to incorporate new concepts you've learned, eliminate redundant processes, if any, and optimize your code for performance and efficiency, thereby laying the groundwork for improvement. Ask yourself: 

• Does the solution code run for all possible inputs?
• Are there any alternate solutions  to the problem code?
• How do I improve the performance and efficiency of the code? Is it possible to reduce the code space and compilation time? 
• How can I make the code more readable? What are the redundant steps that can be struck out?

As you familiarize yourself with useful patterns or problems you faced in the past while solving coding questions, you'll succeed in building yourself a toolkit of solutions to apply to new problems. Learning about the flaws in your code helps you grow as a developer. 

Sometimes, all you need is a fresh set of your eyes to realign your coding perspective. So, don't hesitate to seek help from friends or colleagues if you are facing problems with your code. Your peers may have a better or more optimized framework that you aren't aware of. Allow them to teach you so as to hone your problem solving with algorithms and data structures. This is your best chance to refine your methodologies and get better at coding problems.

Make sure you return the favour if the opportunity ever presents itself. In this manner, you can collectively progress your coding abilities. 

If you are stuck somewhere, look up the solution code only as a last resort. When you do, you are likely to find a specific framework to solve the problem which in turn will serve to disrupt your individualistic problem-solving abilities. So, resist the temptation to look up the solution wherever possible. Think hard and try to arrive at the solution on your own. 

Even if you do go down that road, such as by using a tool like chatgpt, avoid memorizing or taking it down as is; simply familiarize yourself with the logic and attempt to create a new solution based on your learning. 

If there's one sure shot way of getting better at coding problems, it is to practice until you become confident of your problem-solving skills. From brushing up on data structures like arrays, strings, trees, linked lists, and heaps to building competence in search, sort, time complexity algorithms, the end goal is to be able to visualize optimized, logical solutions to any given coding problem. 

Make sure to time yourself so you get a taste of the kind of pressure you'll be expected to tackle at your technical interview. 

You can participate in coding challenges or hackathons so as to assert your readiness. This will also help you find out where your weaknesses lie, and allow you to work towards eliminating them.

Other problem-solving activities you can indulge in on the side are puzzle games, chess, riddles to boost critical and analytical thinking capacities.

Mastering coding is no easy feat. It takes dedicated effort and time. So, don’t beat yourself up if you face obstacles along the way. Just make sure you keep at it, and you will eventually excel at problem solving with algorithms and data structures. We hope this helped you understand how you can get better at coding!