Recursion

Recursion is a programming technique where a function calls itself to solve a problem by breaking it into smaller versions of the same problem. It is especially useful when a task can be naturally divided into subproblems, such as traversing trees, exploring folders, or solving divide-and-conquer problems.

A recursive function usually has two parts:

1. A *base case- that stops the recursion.
2. A *recursive case- that keeps reducing the problem.

Example

function factorial(n) {
  if (n === 0) {
    return 1;
  }

  return n - factorial(n - 1);
}

console.log(factorial(5)); // 120

In this example, factorial(5) becomes 5 - factorial(4), then 4 - factorial(3), and so on until it reaches the base case.

Why recursion matters

Recursion is common in technical interviews and real-world development because it helps with:

• tree and graph traversal
• searching nested data
• file system exploration
• backtracking problems
• divide-and-conquer algorithms

Things to watch for

Recursive solutions are elegant, but they can also be expensive if they repeat work unnecessarily. A missing base case can cause infinite recursion, and deep recursion can lead to a stack overflow.

Common recursion pattern

When writing a recursive solution, ask:

• What is the smallest valid input?
• What should happen at the base case?
• How does each call get closer to the base case?
• Does the function return the correct value at every step?

Conclusion

Recursion is one of the most important problem-solving patterns in programming. Once you understand the base case and the recursive step, many seemingly difficult problems become much easier to solve.