When should I use memoization?

What is memoization and when should I use it?

Memoization is an optimization technique that stores the results of expensive function calls and returns the cached result when the same inputs occur again. You should use it when you have functions that are called frequently with the same arguments, especially in recursive algorithms.

Can you give me an example of a situation where memoization would be beneficial?

Sure! A classic example is calculating Fibonacci numbers. Without memoization, the function recalculates the same Fibonacci numbers multiple times, leading to exponential time complexity. With memoization, you store previously calculated Fibonacci numbers, reducing the time complexity to linear.

Are there any downsides to using memoization?

Yes, while memoization can improve performance, it also uses additional memory to store the cached results. If the input space is large, it can lead to high memory consumption.

How do I implement memoization in JavaScript?

You can implement memoization in JavaScript by creating a function that uses a closure to store results in an object. Here's a simple example:

function memoize(fn) {
    const cache = {};
    return function(...args) {
        const key = JSON.stringify(args);
        if (cache[key]) {
            return cache[key];
        }
        const result = fn(...args);
        cache[key] = result;
        return result;
    };
}