How to Read Code Written by Others
Learn how to read, understand, and learn from other people's algorithmic solutions to improve your own coding skills.
The Art of Reading Code
Writing code is only half the job. A massive part of software engineering and improving at DSA is reading and understanding code written by other people.
Why You Should Read Other Solutions
After you solve a problem on LeetCode, don't immediately move to the next one. Go to the discussion tab and read the top-voted solutions.
- You might have written a 30-line solution, while someone else solved it in 5 elegant lines.
- You might learn a new built-in function you didn't know existed.
- You expose yourself to different paradigms and thought processes.
How to Deconstruct a Solution
When you look at a highly optimized, complex solution, it can be intimidating. Here is how to break it down:
- Identify the Core Pattern: Is this a Two Pointer approach? Is it using a Stack?
- Track the Variables: Look at the variable initializations. What are they keeping track of?
- Dry Run the Logic: Take a simple input and trace it through their code line by line.
Don't Blindly Copy
Understanding a solution is great; copying it into your editor and claiming you "solved" it is detrimental. If you find a better solution, close the tab, and try to recreate that better solution from memory.
The Takeaway
Treat reading other people's code as a free mentorship. By actively analyzing how better programmers solve problems, you will rapidly elevate the quality and efficiency of your own code.
It exposes you to new techniques, more elegant logic, and language-specific features that you might not have discovered on your own.
Focus on variable names, identify the core algorithmic pattern being used, and dry-run the code with a small test case to observe its behavior.
Yes, reading a clean solution in Python can help you understand the logic, which you can then translate into Java or C++.
Not if you have already solved the problem or spent adequate time trying. It is a vital learning resource for optimization.
Use descriptive variable names, maintain consistent indentation, extract complex logic into separate functions, and write concise comments explaining 'why' not 'how'.