The base case tripped me up more than I expected.
Start by clarifying edge cases and input assumptions, then propose sorting the intervals by start time and merging in a single pass. Walk through the algorithm with a concrete example, analyze time and space complexity, and discuss potential optimizations or alternative approaches.
Pro tip: At Meta, interviewers value clean, efficient code and the ability to handle edge cases gracefully. Before coding, explicitly state your assumptions and confirm them with the interviewer to avoid misunderstandings.
Ask about input format, whether intervals are inclusive, if the list can be empty, and if intervals are already sorted. Confirm expected output format.
Explain that sorting by start time allows merging overlapping intervals in a single pass. Mention that you'll iterate through the sorted list, merging when the current interval overlaps with the last merged one.
Choose a small example (e.g., [[1,3],[2,6],[8,10],[15,18]]) and demonstrate step-by-step how the algorithm merges intervals and produces the output.
State that sorting takes O(n log n) time and merging takes O(n), so overall O(n log n) time. Space is O(n) for the output (or O(log n) if sorting in-place). Discuss if input is already sorted, we can skip sorting and achieve O(n).
Write clean code with meaningful variable names, handle edge cases (empty list, single interval), and test with the example and additional cases like non-overlapping intervals.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.