Start by clarifying the problem and edge cases, then propose an efficient algorithm such as sorting start and end times separately and using a two-pointer sweep to count concurrent meetings. Walk through a small example to validate the approach, and discuss time/space complexity.
Pro tip: Mention that the problem is equivalent to finding the maximum number of overlapping intervals, and that the sweep-line algorithm is optimal. Also, briefly discuss how to handle edge cases like empty input or zero-length meetings.
Ask if intervals are inclusive/exclusive, if meetings can be zero-length, and if the input is sorted. Confirm that we need the minimum number of rooms to accommodate all meetings without conflicts.
Propose sorting start and end times separately, then using two pointers to count active meetings. Alternatively, use a min-heap to track end times of ongoing meetings.
Demonstrate the algorithm on a small set of intervals, showing how the count of active meetings changes and how the maximum is tracked.
State that sorting takes O(n log n) time and the sweep takes O(n) time, leading to O(n log n) overall. Space complexity is O(n) for storing start and end arrays or the heap.
Mention handling of empty input, single meeting, all meetings overlapping, and meetings that end exactly when another starts (no overlap).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.