What memoization is
Memoization is a programming technique used to speed up programs by storing the results of expensive function calls and returning the saved result when the same inputs happen again. Instead of recomputing an answer it has already worked out, the program remembers it and reuses it. This can dramatically reduce the amount of repeated work a program does, especially when the same calculations come up many times.
The problem it solves
Some functions are costly to run, and in certain programs the same function is called repeatedly with the same inputs. Without any optimization, each of these calls does the full work again, wasting time. Memoization addresses this by recognizing when an input has been seen before and returning the stored result instead of recalculating. It targets the inefficiency of redoing identical computations over and over.
How memoization works
Memoization works by keeping a store, often called a cache, that maps inputs to their computed results. When the function is called, it first checks whether the result for those inputs is already in the cache. If it is, the stored value is returned immediately. If not, the function computes the result, saves it in the cache, and then returns it. Future calls with the same inputs can then be answered instantly.
A trade-off of time for memory
Memoization makes a deliberate trade: it uses extra memory to store results in order to save time. By keeping past answers around, the program avoids repeating work, which speeds it up. The cost is the memory needed to hold the cached results. In many cases this trade is well worth it, but it means memoization is most useful when the time saved outweighs the memory used.
Memoization and dynamic programming
Memoization is closely related to a broader technique called dynamic programming, which solves complex problems by breaking them into overlapping subproblems and reusing their solutions. Memoization is one natural way to implement this idea, caching the results of subproblems so each is solved only once. This connection is why memoization comes up often in discussions of efficient algorithms for certain kinds of problems.
Why it matters
Memoization is a simple but powerful idea for making programs faster by not repeating work. Understanding what memoization is - caching function results to reuse them for repeated inputs - clarifies a common optimization technique and its link to dynamic programming. For anyone learning to write efficient code, memoization is a valuable concept to understand.
Related on Skillo
See also: What is recursion? Explained, What is Big O notation? Explained.
Sources
Published date reflects the original event date (2023-05-30). This article is original Skillo editorial written from the sources above; facts were verified in September 2026.
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