ConcurrentHashMap compute atomicity
You ask an AI to explain this Java cache so you can extend it. The agent says: "It's a thread-safe lazy-loading cache — ConcurrentHashMap guarantees that even under concurrent access, compute() runs at most once per key." You're about to add an expensive remote call inside compute(). Is the explanation correct, and how would you verify before relying on the at-most-once claim?
Implement
count_compute_calls(request_waves: list[list[str]], atomic: bool) → intExamples
in
[[["k","k","k","k","k","k","k","k"]],false]out8in
[[["k","k","k","k","k","k","k","k"]],true]out1What a strong answer looks like
Treat the AI’s output as a draft to verify, not an answer to trust. Name the specific flaw and the input that triggers it, say how you’d catch it (tests, edge cases, reading critically), and how you’d re-prompt or decompose to get it right.
0:00 of about 20 min
Vibe & agentic: describe the solution in plain language (or narrate it) and the coach grades your approach.
Which questions mattered is sealed until you submit. Telling you now would just be handing over the edge cases.
Run or narrate your approach, then ask the coach.