John Fleetwood (curator)

Recursion in computer science is a method of solving a problem where the solution depends on solutions to smaller instances of the same problem. A recursive function calls itself within its own definition. This process continues until a base case is reached, which is a condition that stops the recursive calls and allows the function to begin returning values. Without a properly defined base case, a recursive function will run indefinitely, leading to a stack overflow error.

The key components of a recursive function are:

• Base Case: A condition that determines when the recursion should stop. This is crucial to prevent infinite loops.
• Recursive Step: The part of the function that calls itself with a smaller or simpler version of the input. This step moves the problem closer to the base case.

Recursion is often used to solve problems that can be broken down into smaller, self-similar subproblems. Examples include traversing tree-like data structures, calculating factorials, and implementing algorithms like quicksort and mergesort.

While recursion can lead to elegant and concise solutions, it can also be less efficient than iterative approaches due to the overhead of function calls and potential stack overflow issues. The choice between recursion and iteration often depends on the specific problem and the programmer's preference and understanding of the trade-offs involved. Understanding the call stack and how it manages recursive calls is important for debugging and optimizing recursive functions.

Recursive functions can be difficult to understand and debug, especially for complex problems. Care must be taken to ensure the base case is correctly defined and that the recursive step correctly reduces the problem towards the base case. Improperly designed recursive functions can lead to significant performance issues or program crashes.