What is memoization and how does it improve performance?

What is memoization and how does it improve performance?

Memoization is an optimization technique that stores the results of expensive function calls and returns the cached result when the same inputs occur again. This can significantly improve performance, especially in recursive algorithms.

Can you give me an example of how memoization works?

Sure! For instance, in calculating Fibonacci numbers, without memoization, the function recalculates values multiple times. With memoization, once a Fibonacci number is calculated, it's stored, so future calls can retrieve it instantly.

What are some common use cases for memoization?

Common use cases include dynamic programming problems, such as calculating Fibonacci numbers, pathfinding algorithms, and caching results in web applications to reduce server load.

Are there any downsides to using memoization?

Yes, while memoization can improve performance, it also consumes more memory to store the cached results. If the input space is large, it can lead to high memory usage.