The sorting part was fine, the annoying bit was remembering to handle the case where fewer than n workers exist for a position without crashing or returning garbage.
Clarify the data model and constraints first, then propose an efficient solution using a heap or sorting with a custom comparator. Discuss trade-offs between approaches and handle edge cases like ties and insufficient workers.
Pro tip: Mention that you would confirm whether the method should be called frequently and if the data changes often, as that determines whether to precompute or compute on the fly. Also, explicitly state how you handle ties and the output format.
Ask about the data structure for workers and hours, expected input size, frequency of calls, and whether the data is static or dynamic. Confirm the tie-breaking rule and output format.
Explain how to compute total hours per worker for the given position, likely by iterating over records and summing hours, possibly using a hash map for efficiency.
Choose between sorting all workers (O(m log m)) or using a min-heap of size N (O(m log N)) for top N. Discuss trade-offs based on N and m.
Define a comparator that sorts by total hours descending, then worker ID lexicographically ascending. Format each result as '<worker_id>(<total_time>)'.
Consider cases where N exceeds the number of workers, no workers for the position, or ties. Walk through an example to verify correctness.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.