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The recursion part tripped me up more than I expected.
Start by clarifying the input format and edge cases, then propose a solution that compares consecutive stack samples to detect changes, using a stack of active frames to manage start/end events. Emphasize handling recursion by tracking depth and avoiding duplicate events for identical stacks.
Pro tip: Mention that you would use a stack data structure to track active frames and compare with the previous sample, and explicitly call out how you handle recursion by including depth in the frame identity. This shows you understand the subtlety of the problem and can communicate complex ideas clearly.
Ask questions to confirm input format (e.g., list of stacks, each stack a list of function names from bottom to top), output format (list of events with type, function, timestamp), and how to handle recursion and identical stacks. Discuss assumptions about timestamps and whether events should have timestamps.
Propose maintaining a stack of active frames (with function name and depth) and iterating through samples. For each sample, compare with the previous stack to find the deepest common prefix, then emit end events for frames that are no longer present (from innermost to outermost) and start events for new frames (from outermost to innermost).
Explain that recursive calls are distinguished by their depth in the stack, so when comparing stacks, you compare element by element including position. Identical consecutive stacks produce no events because the common prefix is the entire stack.
Write pseudocode or actual code, then walk through examples: a simple call, a recursive call, and a case with identical stacks. Test edge cases like empty stacks, functions appearing/disappearing at different depths, and functions still running at the end.
Discuss time complexity O(N*M) where N is number of samples and M is average stack depth, and space complexity O(M) for the active stack. Mention potential optimizations like using a persistent data structure or hashing stacks, but note that simplicity is often preferred.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This is where I started to feel the time pressure.
First, clarify the debouncing semantics: define what counts as 'same position' and how to handle interruptions. Then, design a state machine that tracks consecutive samples per frame and emits a start event only after N consecutive matches, choosing the timestamp source based on product requirements. Finally, ensure recursion still works by treating the debounced start as the new trigger and handling nested frames correctly.
Pro tip: Explicitly state your assumption about the timestamp source (first vs Nth sample) and justify it based on latency vs accuracy trade-offs; this shows you think about product impact, not just code.
Ask questions to pin down 'same position' (exact match? tolerance?), what happens if the frame moves before N samples, and whether N is per-frame or global. Also confirm if recursion should apply to the debounced events or raw samples.
Propose a data structure (e.g., a map from frame ID to a counter and first-seen timestamp) to track consecutive occurrences. Explain how to reset the counter when the frame moves or disappears.
Describe the logic: when a frame is detected, increment its counter; if counter reaches N, emit a start event. Choose timestamp source (first or Nth sample) and justify. Handle cases where multiple frames overlap.
Explain that recursion should operate on the debounced start events, not raw samples. Show how to avoid infinite loops and ensure nested frames are processed with the same N-consecutive rule.
Discuss time/space complexity (O(1) per sample with hash map) and trade-offs: larger N reduces false positives but increases latency. Mention configurability and potential optimizations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.