What are the applications of memoization in programming?

What are the applications of memoization in programming?

Memoization is a technique used to optimize functions by storing previously computed results. It's commonly applied in recursive algorithms, dynamic programming, and caching.

Can you give me an example of where memoization is particularly useful?

Sure! A classic example is the Fibonacci sequence. Without memoization, it has exponential time complexity, but with memoization, it can be computed in linear time.

Are there any downsides to using memoization?

Yes, while memoization can improve performance, it also consumes more memory to store results, which can be a downside in memory-constrained environments.

How does memoization differ from caching?

Memoization is a specific form of caching that stores results of function calls, while caching can refer to storing any type of data for faster access.

In what programming languages is memoization commonly used?

Memoization is commonly used in languages like Python, JavaScript, and Ruby, where functions can be first-class citizens and closures are supported.