The basic idea clicks fast: sort by length descending, grab index 2.
Clarify the ranking rule: sort words by length descending, but for equal lengths, keep original order (stable sort). Then return the third word in the sorted list, handling edge cases like fewer than three words or duplicate lengths.
Pro tip: Mention that you can use a stable sort or a min-heap of size 3 to achieve O(n) time, but always confirm the expected time/space complexity with the interviewer.
Ask about empty input, fewer than three words, and whether 'third largest' means third distinct length or third word. Confirm that ties preserve original order.
Decide between sorting (O(n log n)) or a min-heap of size 3 (O(n)). Explain the trade-offs and pick based on constraints.
If sorting, use a stable sort (e.g., Python's sorted with key=len, reverse=True). If using a heap, store (length, index) to break ties by original order.
Return null or an empty string if there are fewer than three words. Ensure the third element is correctly identified after sorting.
Walk through examples, including ties and duplicates, to confirm the output matches the expected third largest word.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.