Question
Simulate a sliding-window-log rate limiter. You are given `requests`, a list of integer arrival timestamps in non-decreasing order, a window length `window`, and a `limit`. A request at time t is ALLOWED iff, counting it, at most `limit` requests fall within the half-open window (t - window, t] (i.e. timestamps strictly greater than t-window and up to t, among requests that were themselves allowed). Rejected requests do not occupy the window. Return a list of booleans, one per request, indicating allowed (True) or rejected (False).
sliding_log_limiter(requests: list[int], window: int, limit: int) → list[bool][[1,2,3,4],3,2]out[true,true,false,true]State your approach and its time/space complexity out loud before you optimize. Handle the edge cases (empty input, duplicates, overflow), and say why you chose this over the brute force. Green tests are the floor, not the grade.
Vibe coding: describe the solution in plain language (or narrate it) and the coach grades your approach. Generating runnable code from your description is coming next.