Implementing Memoization for Performance Optimization in JavaScript

When dealing with computationally expensive operations, optimizing your code is crucial. Memoization is a powerful optimization technique that stores the results of function calls and reuses them when the same inputs occur again. This avoids unnecessary re-computation, improving performance significantly, especially in recursive or frequently executed functions.

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In this article, you’ll learn how to implement memoization, explore use cases, and understand when it is most effective.

1. What is Memoization?

Memoization involves caching the result of a function call based on its inputs. If the function is called again with the same input, the cached result is returned instead of recalculating it. This is especially useful in recursive algorithms like the Fibonacci sequence or expensive calculations that are invoked repeatedly.

2. A Simple Example: Fibonacci Sequence

The Fibonacci sequence is a common problem that benefits from memoization. Without memoization, calculating Fibonacci numbers can result in redundant computations, leading to poor performance.