My first instinct was to iterate per-person and intersect free windows, which works but gets messy fast when intervals overlap within a single person's schedule.
Clarify the problem constraints and edge cases, then propose an efficient algorithm that merges all busy intervals, computes free intervals within the window, and filters by minimum duration. Discuss time/space complexity and potential optimizations.
Pro tip: Mention that intervals are half-open to avoid off-by-one errors, and consider using a sweep line or sorting approach for efficiency. Also, discuss how to handle large inputs or streaming data if relevant.
Ask about interval inclusivity, window boundaries, minimum duration, and whether intervals can be empty or overlap. Confirm output format (e.g., list of intervals).
Decide between merging all busy intervals then finding gaps, or using a sweep line with events. Consider sorting all intervals by start time.
Merge overlapping busy intervals, clip to the window, compute free intervals, and filter those shorter than the minimum duration. Ensure half-open interval logic.
State time and space complexity (e.g., O(N log N) due to sorting). Discuss potential improvements for large N or if intervals are already sorted.
Walk through a simple example to verify correctness, including edge cases like no free slots or free slots exactly at the minimum duration.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.