Start by clarifying the problem constraints (e.g., whether intervals are sorted, inclusive/exclusive endpoints). Then propose sorting intervals by start time and merging in a single pass, explaining the logic and edge cases. Finally, analyze time and space complexity and discuss potential optimizations or variations.
Pro tip: Mention that sorting is often the bottleneck and that if intervals are already sorted, merging can be done in O(n) time. Also, proactively discuss how to handle edge cases like empty input or intervals that touch at endpoints.
Ask about input format (sorted or unsorted, inclusive/exclusive endpoints), output format, and edge cases like empty array or single interval. This shows attention to detail and avoids assumptions.
Explain that you will sort intervals by start time, then iterate through them, merging overlapping intervals into a result list. Mention that sorting is key to simplifying the merge logic.
Use a small example (e.g., [[1,3],[2,6],[8,10],[15,18]]) to demonstrate the algorithm step by step, showing how intervals are merged and added to the result.
State that sorting takes O(n log n) time and merging takes O(n) time, so overall O(n log n) time and O(n) space for the output (or O(1) extra space if done in-place).
Cover edge cases like empty input, intervals that touch at endpoints, and already sorted input. Mention that if input is sorted, the solution can be O(n) time.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.