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What Is Recursion?
Recursion is when a function calls itself to solve a problem by breaking it into smaller subproblems. Every recursive function has a base case (when to stop) and a recursive case (how to break down the problem). It naturally solves problems with self-similar structure: trees, fractals, nested data.
How Recursion Works
Factorial: factorial(5) = 5 * factorial(4) = 5 * 4 * factorial(3) ... until factorial(1) = 1 (base case). File system traversal: to list all files, list files in the current directory, then recursively list files in each subdirectory.
Recursive thinking: if you can solve the problem for n-1, can you use that to solve it for n? That's recursion. Tree traversal, merge sort, quicksort, and many graph algorithms are naturally recursive.
Key Concepts
- Base Case — The condition that stops recursion — without it, you get infinite recursion and stack overflow
- Recursive Case — The part that breaks the problem down and calls the function again with a smaller input
- Call Stack — Each recursive call adds a frame to the stack — too many calls cause stack overflow
- Tail Recursion — Recursion where the recursive call is the last operation — some languages optimize this to avoid stack overflow
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Frequently Asked Questions
Recursion vs iteration?
Any recursive solution can be written iteratively (using loops and a stack). Recursion is more elegant for tree/graph problems. Iteration is usually faster and uses less memory. Use whichever is clearer.
How do I think recursively?
Ask: what's the simplest case I can solve directly? (base case). Can I express the solution in terms of a smaller version of the same problem? (recursive case).
Want a structured learning path?
Plan a Recursion Lesson →