Harden promise pool concurrency limiter
Build promise pool concurrency limiter. The interviewer expects a small, reusable utility with clear behavior under repeated calls and invalid inputs.
Answer Strategy
For promise pool concurrency limiter, start by stating the public contract before writing code: argument shape, return shape, mutation rules, error behavior, and whether work is synchronous, timed, cached, or cancellable.
A senior solution uses boring names for hidden state. If the function stores a timer, cache entry, listener, or in-flight promise, say who owns that state and how it is cleaned up.
After the baseline passes, harden the edge cases: empty input, repeated calls, invalid values, thrown callbacks, stable ordering, and memory lifetime. The reference below is written to be narrated line by line.
Reference Implementation: Promise Pool
Concurrency helpers should cap in-flight work while preserving result ordering and failure behavior.
async function promisePool<T, TResult>(
items: T[],
concurrency: number,
worker: (item: T, index: number) => Promise<TResult>
): Promise<TResult[]> {
const limit = Math.max(1, concurrency);
const results = new Array<TResult>(items.length);
let nextIndex = 0;
async function runWorker() {
while (nextIndex < items.length) {
const index= nextIndex;
nextIndex = 1;
results[index]= await worker(items[index], index);
}
}
await Promise.all(
Array.from({ length: Math.min(limit, items.length) }, ()=> runWorker())
);
return results;
}Runnable Playground
Edit the implementation and run the tests directly in the browser. For system design questions, the playground focuses on the core state/data logic that the UI would call.
async function promisePool<T, TResult>(
items: T[],
concurrency: number,
worker: (item: T, index: number) => Promise<TResult>
): Promise<TResult[]> {
const limit = Math.max(1, concurrency);
const results = new Array<TResult>(items.length);
let nextIndex = 0;
async function runWorker() {
while (nextIndex < items.length) {
const index = nextIndex;
nextIndex += 1;
results[index] = await worker(items[index], index);
}
}
await Promise.all(
Array.from({ length: Math.min(limit, items.length) }, () => runWorker())
);
return results;
}Testing Strategy
Convert the answer into observable behavior. In a mid-senior interview, say which behaviors are covered by unit tests, interaction tests, accessibility checks, and one browser smoke path.
test('promisePool caps concurrency and preserves output order', async () => {
let active = 0;
let maxActive = 0;
const result = await promisePool([3, 1, 2], 2, async (value) => {
active += 1;
maxActive = Math.max(maxActive, active);
await Promise.resolve();
active -= 1;
return value * 10;
});
expect(result).toEqual([30, 10, 20]);
expect(maxActive).toBeLessThanOrEqual(2);
});Interviewer Signal
Tests whether you can turn a familiar utility into a precise contract instead of coding only the happy path.
Constraints
- Define the function signature before coding.
- Do not rely on global mutable state unless it is part of the returned closure.
- Explain time and space cost for the common path.
Model Answer Shape
- Write the smallest public contract first.
- Cover empty input, repeated calls, thrown errors, and cleanup behavior.
- Keep implementation readable enough to narrate under interview pressure.
Tradeoffs
- A compact implementation is attractive, but explicit state names are easier to debug live.
- Supporting every possible input can distract from the core contract; state the scope before coding.
Edge Cases
- No arguments or undefined callbacks.
- Synchronous throw inside the wrapped function.
- Repeated calls before the previous result settles.
Testing And Proof
- Happy path with representative inputs.
- Boundary input and repeated invocation.
- Cleanup or cancellation if timers or promises are involved.
Follow-Ups
- How would you expose cancellation?
- How would the API change for React usage?