The negating the score trick for descending sort is something I knew but fumbled explaining out loud.
Clarify the sorting requirements and edge cases, then propose a comparator-based approach that handles all three keys in order. Discuss the time complexity and whether a stable sort is needed, and consider if any optimizations or alternative data structures are relevant.
Pro tip: Mention that you would use a stable sort to preserve the original order for ties beyond the specified keys, and that you would write unit tests for edge cases like empty lists or missing translations.
Ask about the expected input size, whether the list can be empty, if candidate translations can be empty, and if the sort should be stable. Confirm the exact sorting order and tie-breaking rules.
Define a comparator that first compares scores in descending order, then source words alphabetically, then the length of the first candidate translation ascending. Handle cases where candidate translations list is empty.
Discuss that comparison-based sorting is O(n log n) and that the comparator runs in O(1) time (assuming string comparisons are constant time). Mention that a stable sort like Timsort (Python's default) is suitable.
Write clean code using the language's built-in sort with a custom key or comparator. Test with edge cases: empty list, equal scores, equal source words, empty candidate translations, and varying lengths.
Consider if the list is huge and memory is a concern, or if we can precompute the length of the first candidate translation to avoid repeated access. Mention that if the list is already partially sorted, adaptive sorts perform better.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.