← Bloomberg Interview Insights
The trick I kept second-guessing myself on was whether to use a min-heap or just sort and scan.
Clarify the problem and edge cases, then propose an efficient solution using a min-heap to track end times. Explain the algorithm step-by-step, analyze time and space complexity, and discuss potential optimizations or alternative approaches.
Pro tip: Mention that the heap approach is optimal for large inputs and that sorting is necessary; also note that the problem is equivalent to finding the maximum number of overlapping intervals at any point.
Ask about input format, whether intervals are inclusive/exclusive, and handle empty input or single meeting.
Sort intervals by start time, use a min-heap to track end times of ongoing meetings, and allocate rooms as needed.
Demonstrate the algorithm on a sample input to show how rooms are allocated and freed.
State that sorting takes O(n log n) and heap operations take O(n log n), resulting in O(n log n) time and O(n) space.
Mention the sweep line approach with separate start/end arrays, and compare simplicity vs. efficiency.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.