Programming challenges and competitions are a great way to test your skills, learn new techniques, and have fun with other coders. But how do you tackle them effectively and efficiently, without compromising on creativity and quality? In this article, we'll share some tips and strategies that can help you solve programming problems faster, smarter, and better.
The first step to solving any programming challenge is to understand the problem clearly and completely. Read the instructions carefully, identify the inputs and outputs, and check the examples and edge cases. If possible, restate the problem in your own words or draw a diagram to visualize it. This will help you avoid confusion, ambiguity, and unnecessary complexity later on.
1.If you can draw the problem and map input and output on a paper, its 80% resolved. 2. If you have truth table for the problem, take all kinds of input to cover all edge/corner cases. 3.When understanding problem, also understand the pattern, so that algorithm you write will be true for all similar inputs giving you 100% error free program everytime for all values. 4. Last and very important step in understanding problem is to be able to come with a solution in your mind. While doing it, your understanding should be to the point that there is no confusion about the program flow or ambiguity about input or output.
Practice, Exposure, knowledge, expertise, discussions, all factors count here. To do it quickly and efficiently, 1. Plan it. How to approach the problem. 2. Research it. How other experts are doing it. 3. Discuss it. Take feedback on your solution and add improvements. 4. Write it and later optimize it. In my personal opinion, step 1 is most important, without planning, it takes more time because steps are not clear in mind.
Oh man I don’t think that’s a good approach. That sounds like test first development only you are starting at the requirements phase? That sounds like a lot of work for something that has a 70% chance of being vaporware. I say if you have a good insight or approach just start building the mvp. Hack some thing together on a long weekend and then show it to the team. If it’s getting tacos approval then get feedback and then make the necessary changes. Then you can talk about requirements, Jira documents and other business stuff because you’ll have some idea of the major pitfalls that were about to make you look dumb after the first sprint cycle or whatever. Plus if it’s a train wreck just burn the evidence, and never speak of it again.
If you have the leisure of having more than one day to look at the issue, make sure to try to understand the problem and then come back to it one day later, giving your brain time to process the problem will be a huge payoff later when implementing the solution and will probably help you catch something you missed on your first read.
According to my experience, if you solved several challenges before, you can detect similar problems and understand the problem faster. You can also find a solution that merges 2 or more you used before. Practice is important.
The next step is to choose the right tools for the job. Depending on the nature and difficulty of the problem, you might need to use a specific programming language, framework, library, or algorithm. Consider the pros and cons of each option, and how they fit with the requirements and constraints of the challenge. For example, if you need to optimize for speed, you might want to use a low-level language like C or C++. If you need to handle complex data structures, you might want to use a functional language like Haskell or Scala.
Keep the problem domain isolated from the solution domain to avoid the "Man with a Hammer" syndrome; e.g. "I know Java well" usually is NOT a good reason for choosing a solution. Instead, first make the problem clear and choose the solution only AFTER understanding various aspects of the problem.
Of course to choose the most suitable tool comes from understanding the problem itself, so the tools would be more useful for solution process
Here is where experience shines. To often you will here, is that language better? IS that DB better? There’s is no this better than that, there is what’s best for this problem and the answer can only come if you hold a solid breath of knowledge. So get dirty and play with everything, read technical articles, ask peers!! Don’t be embarrassed to ask your peers!!
The choice of tools is an important stage in the implementation of a solution to a problem. It is quite correctly noted that the tools for implementing the solution must be chosen based on the generated solution path (input / output data, patterns, algorithms, data structures and solution requirements) - the choice of programming language, framework, library, architecture. As correctly noted, the solution and the requirements for it determine the optimal tools for implementing the solution itself.
Certainly, selecting the appropriate tools isn't a straightforward rule. To become skilled at making these choices, you must gain experience through hands-on work, both with your own projects and by studying others' experiences shared in engineering blogs and similar resources.
Once you have the tools, you need to break down the problem into smaller and simpler subproblems. This will help you focus on one aspect at a time, and make it easier to test and debug your code. You can use techniques like divide and conquer, recursion, or dynamic programming to split the problem into manageable chunks. For example, if you need to sort a list of numbers, you can use a recursive algorithm like merge sort or quick sort to divide the list into halves, sort them separately, and merge them back together.
This technique works all the time, even at work being able to break down the problem into small manageable pieces helps you not get overwhelmed. And yes when dealing with a challenge the strategy works too as you can build up to your solution solution, especially if this is a live coding question.
Actually to break down the issues into small pieces that would be more to manage and more faster to solve like for example we can break one problem to many small blocks for easy control and later we can build these blocks for the whole problem.
There’s no secret sauce here and you can’t cheat. You have to put in the effort of dissecting the problem and breaking it down to its core. Plan the work, work the plan.
The technique of dividing tasks into smaller tasks is, in most cases, the best way to concertize the implementation of a solution. The formation of smaller tasks with the definition of input and output data for each stage (module, block) allows you to create the ability to control and verify each part (block, module) of the solution. As a result, this allows you to quickly release the solution, reduce or even eliminate the occurrence of errors (including logical ones), and also make it possible to easily upgrade the solution.
Breaking down a problem into smaller parts and structuring them in a logical sequence is vital. It simplifies complex tasks, helps manage dependencies, and forms a clear path for problem-solving. This approach enhances efficiency and makes it easier to tackle each component effectively.
Now that you have the subproblems, you need to write and test code for each one. You can use an online editor or IDE to write your code, or use a local environment if you prefer. Make sure you follow good coding practices, such as using meaningful names, commenting your code, and formatting it properly. You can use tools like linters, code analyzers, or code formatters to help you with that. To test your code, you can use built-in or external tools like unit testing frameworks, debugging tools, or online judges. You can also use your own test cases or examples to check your logic and output.
Unit tests are for developers. No one will ever see your code except other developers. The boss doesn’t care that your loop of a million records completed in less than half second because of your efficient code. Your peers will love you for your clean, TESTABLE code. So write your unit tests! Name then something that makes sense to them not to you, and make sure they pass lol.
It is very important to write "readable" code. After all, following the rules for writing code will make it easy to maintain your own code, and the use of linters, IDE will save time. And after 6 months you will easily understand what this function is for. Also, use the principles of writing code - DRY, KISS, SOLID, etc. This always allows you to organize the structure of the code more logically and efficiently. Be responsible and don't write "bad smelling code"! It is rightly noted that code testing is the responsibility of the programmer. Tests allow you to make sure that your code works as expected and according to the requirements. And in case the code doesn't work as expected, you can easily find where it happened and why.
The final step is to refine and optimize your code. You can do this by reviewing your code for errors, bugs, or inefficiencies, and making improvements where necessary. You can use tools like code reviewers, code analyzers, or performance profilers to help you with that. You can also use techniques like refactoring, modularization, or abstraction to make your code more readable, reusable, and maintainable. You can also use techniques like memoization, caching, or parallelization to make your code more efficient and scalable.
It is rightly noted that the stage of refactoring and optimizing the solution will allow you to make changes and make the code more reusable, etc. Very often, the optimization stage is necessary after changing the requirements for the solution or changes in the operation of services that do not depend on you. When optimizing a solution, don't forget to use refactoring patterns and keep in mind the balance between a good and a better solution. Also, before starting optimization and refactoring, I would recommend taking a break, and only after that, looking at the code with a fresh look, take on its analysis and optimization.
See the previous step (unit testing) because the reinvestment stage will almost never come. We would all love to say that we practice refactoring but it’s simply not true. Debt usually gets paid at the end not up front, so if you can do a great job at the unit testing phase, and you never get to refinement…. IT is what IT is.
Solving programming challenges is not only a way to showcase your skills, but also a way to have fun and learn new things. You can enjoy the thrill of solving a problem, the satisfaction of writing a good code, and the feedback of other coders. You can also learn from your own mistakes, from other solutions, and from new concepts and techniques. You can use platforms like HackerRank, Codeforces, or LeetCode to find and join programming challenges and competitions that suit your interests and goals.
Programming is fun, so practice it, learn it, solve complex problem but don't feel pressure, sometimes some problem can take time to get solved but it is totally fine. A slow but good solution is better than than a quick buggy solution. Practice on LeetCode and HackerRank etc these platforms are really good.
Having fun doing anything is one of the strongest driving factors to improve and excel at something. Not every one is fit to be a developer, and it’s ok, but if you find that challenges on HackerRank, project Euler and other similar platform drives you, then keep on drilling. Practice makes perfect.
Having fun and maintaining a learning mindset is a key strategy for solving programming challenges quickly, creatively, and with quality. When you enjoy the process, problem-solving becomes more engaging, and your creativity is sparked. This positive mindset encourages you to explore different approaches and think outside the box, fostering innovative solutions. Learning continuously, whether it's new programming languages, algorithms, or problem-solving techniques, equips you with a diverse set of tools to tackle challenges efficiently. It's a dynamic cycle – the more you enjoy learning, the more creative and skilled you become, leading to quicker and higher-quality solutions.