Recursion vs Iteration: When to Use Which

Many algorithms can be written either recursively (function calls itself) or iteratively (loops). Each has tradeoffs in clarity, stack use, and performance. This post helps you choose and use both well.

Recursion in short

What: A function that calls itself (directly or indirectly) with a smaller or simpler input until a base case is reached.
Pros: Often matches the problem structure (trees, divide-and-conquer, backtracking); can be very readable.
Cons: Stack space (one frame per call); risk of stack overflow for deep recursion; sometimes slower due to call overhead.

Iteration in short

What: Loops (for, while) and explicit state (variables, maybe a stack or queue) instead of recursive calls.
Pros: No extra stack depth; usually predictable memory; often faster in strict languages.
Cons: Can be more verbose for problems that are naturally recursive (e.g. tree traversal, recursive definitions).

When recursion fits well

Naturally recursive structures: Trees, graphs (e.g. “process node, then recurse on children”). Code often reads clearly: “handle this node, recurse for subtrees.”
Divide and conquer: Merge sort, quicksort, binary search — “solve half, combine” maps cleanly to recursion.
Backtracking / enumeration: Try a choice, recurse, undo. Recursion keeps the “current state” on the call stack.
Depth is bounded: Directory trees, expression trees, or problem sizes that don’t go very deep. Then stack overflow is unlikely.

When to prefer iteration

Tail recursion: If the only thing after the recursive call is returning its result, you can rewrite as a loop (many languages don’t optimize tail recursion, so iteration avoids stack growth).
Very deep recursion: Large inputs or deep structures (e.g. long list, deep tree) — iteration with an explicit stack avoids stack overflow.
Performance-critical hot path: Loops avoid call overhead and can be easier for the runtime to optimize.
Single pass, simple logic: “Do X for each element” is usually clearer and cheaper as a loop.

Converting recursion to iteration

Tail recursion: Replace with a loop; use variables for the “current” arguments and update them each iteration.
Non-tail recursion: Use an explicit stack (or queue) that holds “work to do” (e.g. nodes to visit). Simulate the call stack by pushing state before “recurse” and popping to “return.”

Summary

Recursion fits naturally recursive problems (trees, divide-and-conquer, backtracking) and is often clearer; watch stack depth and call overhead.
Iteration avoids stack growth, gives predictable memory, and is often faster; use it for tail-recursive or very deep cases, or when a simple loop is clearer.
You can convert recursion to iteration (tail → loop; general → explicit stack/queue) when you need to avoid deep recursion or squeeze performance.