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Went with a frequency map, count occurrences, then filter.
Start by clarifying the problem: confirm whether the list can contain duplicates, negative numbers, and whether the output should be sorted or in any order. Then propose an efficient solution using a hash map to count frequencies, and iterate through the map to collect numbers with even counts. Discuss time and space complexity, and consider edge cases like empty list or all unique numbers.
Pro tip: Mention that you would use a hash map for O(n) time, but also note that if memory is constrained, sorting the list first (O(n log n)) could be a trade-off. This shows awareness of engineering trade-offs beyond just the optimal solution.
Ask about input constraints, expected output format, and whether the list can be modified. Confirm if numbers appearing zero times (i.e., not in list) should be considered.
Decide between hash map (for O(n) time) or sorting (for O(n log n) time but O(1) extra space). Explain your choice based on typical constraints.
Write code to count frequencies using the chosen data structure, then iterate to collect numbers with even counts. Handle edge cases like empty list.
State time and space complexity of your solution. Discuss potential optimizations or alternative approaches.
Walk through a few test cases, including duplicates, all unique, and empty list, to verify correctness.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.