Write MSW handlers for transfer lifecycle states
Mock success, slow pending, backend empty while local pending exists, retryable error, and reconciliation completion.
Answer Strategy
For write MSW handlers for transfer lifecycle states, 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: Memoize With TTL
This pattern covers the common interview utility shape: a small public API, private closure state, and tests for repeated calls.
type CacheEntry<T> = {
value: T;
expiresAt: number;
};
function memoizeWithTtl<TArgs extends unknown[], TResult>(
fn: (...args: TArgs) => TResult,
ttlMs: number,
keyOf: (...args: TArgs) => string = (...args) => JSON.stringify(args)
) {
const cache = new Map<string, CacheEntry<TResult>>();
return (...args: TArgs): TResult => {
const key = keyOf(...args);
const cached = cache.get(key);
const now = Date.now();
if (cached && cached.expiresAt > now) return cached.value;
const value = fn(...args);
cache.set(key, { value, expiresAt: now + ttlMs });
return value;
};
}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.
type CacheEntry<T> = {
value: T;
expiresAt: number;
};
function memoizeWithTtl<TArgs extends unknown[], TResult>(
fn: (...args: TArgs) => TResult,
ttlMs: number,
keyOf: (...args: TArgs) => string = (...args) => JSON.stringify(args)
) {
const cache = new Map<string, CacheEntry<TResult>>();
return (...args: TArgs): TResult => {
const key = keyOf(...args);
const cached = cache.get(key);
const now = Date.now();
if (cached && cached.expiresAt > now) return cached.value;
const value = fn(...args);
cache.set(key, { value, expiresAt: now + ttlMs });
return value;
};
}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('utility caches repeated calls by contract key', () => {
let calls = 0;
const add = memoizeWithTtl((a: number, b: number) => {
calls += 1;
return a + b;
}, 1000);
expect(add(1, 2)).toBe(3);
expect(add(1, 2)).toBe(3);
expect(calls).toBe(1);
});Interviewer Signal
The mock scenarios should map directly to user-visible states.
Constraints
- Keep local, backend, wallet, chain, and user-visible state distinct.
- Name the product risk before naming the component.
- Tie the answer back to testing or rollout safety.
Model Answer Shape
- Mock success, slow pending, backend empty while local pending exists, retryable error, and reconciliation completion.
- Use explicit ownership boundaries for state, data, and user intent.
- Describe how the UI prevents misleading certainty during pending or failed operations.
Tradeoffs
- Finance-grade UI should be conservative about certainty and optimistic about continuity.
- Local state improves recovery but must not pretend to be canonical business truth.
Edge Cases
- Refresh during pending work.
- Duplicate user intent.
- Backend, wallet, and chain disagree temporarily.
Testing And Proof
- State transition test.
- Reload recovery scenario.
- Accessible status and copy review.
Follow-Ups
- What would you log for support?
- How would you roll this out behind a flag?
Deep Finance Practice
This item has an authored finance specialization page with the original prompt, solution, and any available runnable harness.
Open legacy practice #402 ->