Memoization
Memoization is an optimization technique used in computer programming to speed up function calls by caching the results of expensive computations and returning the cached result when the same inputs occur again. It is commonly applied in dynamic programming, recursive algorithms, and functional programming to avoid redundant calculations. This technique trades memory usage for improved execution time, making it particularly useful for problems with overlapping subproblems.
Developers should learn and use memoization when dealing with functions that are computationally expensive, have repeated calls with the same arguments, or involve recursive algorithms with overlapping subproblems, such as in Fibonacci sequence calculations, factorial computations, or pathfinding in graphs. It is essential for optimizing performance in scenarios like web applications with heavy data processing, game development for AI pathfinding, or financial modeling where calculations are repeated frequently, as it can reduce time complexity from exponential to linear in many cases.