Programming Concepts Intermediate

What is Memoization?

An optimization technique that caches function results for given inputs, avoiding redundant computations for repeated calls.

Memoization stores the results of expensive function calls and returns the cached result when the same inputs occur again. In Python: @functools.lru_cache decorates a function to automatically memoize results.

Memoization is key to dynamic programming, where overlapping subproblems would otherwise cause exponential time complexity. Classic examples include Fibonacci numbers (O(2^n) → O(n)), pathfinding, and string matching. It trades memory for speed.

Related Terms

DRY (Don't Repeat Yourself)

A software development principle that aims to reduce code duplication by abstracting common patterns into reusable components.

A data structure that maps keys to values using a hash function, providing average O(1) time complexity for lookups, insertions, and deletions.

Dependency Injection

A design pattern where objects receive their dependencies from external sources rather than creating them internally.

A surface indication in code that usually corresponds to a deeper problem in the system, suggesting the need for refactoring.

A data structure that follows Last-In-First-Out (LIFO) ordering, where elements are added and removed from the same end (top).

Singleton Pattern

A design pattern that restricts a class to a single instance and provides a global point of access to that instance.

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