How do closures enable memoization

0-2 years experience

1. 1Write a tiny function that returns the nth Fibonacci number using a closure to memoize previous results. How does the closure keep the cache alive?
2. 2If you call that memoized Fibonacci function twice with the same argument, what will be logged if you added a console.log inside the original recursive calculation?
3. 3What would happen if you accidentally declared the cache variable outside the closure instead of inside it?

2-5 years experience

1. 1In a React component you added a memoized helper that computes an expensive layout value. The component re‑renders more often than expected. How would you use a closure to keep the memoization across renders, and what pitfalls could break it?
2. 2A teammate’s closure‑based memoizer is leaking memory because the cache never expires. How would you modify the closure to limit cache size, and what trade‑offs does that introduce?
3. 3You notice the memoized API wrapper sometimes returns stale data after the underlying data changes. Explain why the closure might be the cause and how you’d fix it.

5-8 years experience

1. 1Design a Node.js module that provides memoized database query results across multiple request handlers. Discuss how you’d structure the closure, handle cache invalidation, and ensure safety in a clustered environment.
2. 2Under high load your closure‑based memoization layer shows increased latency due to cache contention. What architectural changes could you make to improve scalability?
3. 3How would you instrument a closure memoizer to track hit/miss ratios and decide when to evict entries in production?

8+ years experience

1. 1Our legacy monolith contains many ad‑hoc closure memoizers. We want to replace them with a centralized caching service. Outline a migration plan, including abstraction of the closure pattern, backward compatibility, and avoiding performance regressions.
2. 2At the organization level, we need to choose between closure‑based memoization in JavaScript services and an external distributed cache like Redis. What factors drive that decision, and how would you evaluate latency, consistency, and developer ergonomics?
3. 3Propose a policy for when engineers should use closure memoization versus other caching strategies across teams, considering maintainability, testability, and cross‑team impact.