What is memoization?
Assesses fundamental understanding of JavaScript conventions, runtime behavior, and memory/performance considerations.
Hiring managers look for precision, avoidance of ambiguous jargon, and ability to explain trade-offs under real production conditions.
Memoization is a functional programming technique which attempts to increase a function’s performance by caching its previously computed results. Each time a memoized function is called, its parameters are used to index the cache. If the data is present, then it can be returned, without executing the entire function. Otherwise the function is executed and then the result is added to the cache.
Let's take an example of adding function with memoization,
const memoizeAddition = () => {
let cache = {};
return (value) => {
if (value in cache) {
console.log("Fetching from cache");
return cache[value]; // Here, cache.value cannot be used as property name starts with the number which is not a valid JavaScript identifier. Hence, can only be accessed using the square bracket notation.
} else {
console.log("Calculating result");
let result = value + 20;
cache[value] = result;
return result;
}
};
};
// returned function from memoizeAddition
const addition = memoizeAddition();
console.log(addition(20)); //output: 40 calculated
console.log(addition(20)); //output: 40 cached
Candidate Response Strategy & Interview Tips
- Start with a concise one-sentence summary: Deliver a direct, confident answer first before expanding into nuances.
- Demonstrate real-world trade-offs: Discuss where this approach excels and when you would avoid it in production systems.
- Discuss complexity & edge cases: Proactively explain time/space complexity or boundary conditions (null values, scale limits).
- Prepare for interviewer follow-ups: Technical hiring panels frequently probe deeper into concurrency, backward compatibility, or alternative libraries.