The array size being ~75 is a hint they don't need an O(n log n) solution but they still want you thinking about it.
First, clarify the requirements and constraints, then propose an efficient in-place algorithm that removes duplicates while preserving the first occurrence, followed by a custom sorting algorithm like quicksort or mergesort. Discuss time and space complexity, and consider edge cases such as all elements being duplicates or the array being already sorted.
Pro tip: Mention that you would use a hash set to track seen elements for O(n) duplicate removal, but if memory is constrained, an in-place approach with nested loops is possible. For sorting, emphasize that you would implement a stable sort like mergesort to maintain the relative order of first occurrences, though the problem doesn't require stability after deduplication.
Ask if the array can be modified in-place, if additional data structures are allowed, and if the order of non-duplicate elements matters before sorting. Confirm that 'zero out' means replace duplicates with 0, and that the final array should be sorted with zeros at the end? Actually, zeros are values, so they will be sorted along with others. Clarify if zeros should be considered as regular values or removed.
Choose an approach: either use a hash set to track seen elements and replace duplicates with 0, or sort first and then remove duplicates. Since sorting is required anyway, you could combine: sort first, then remove duplicates in a single pass, but that changes the 'first occurrence' meaning. So better to remove duplicates first while preserving first occurrence, then sort.
Select an efficient sorting algorithm like quicksort (average O(n log n)) or mergesort (stable O(n log n)). Explain the choice based on constraints: quicksort is in-place but not stable; mergesort is stable but requires extra space. Since stability isn't required after deduplication, quicksort is suitable.
State time complexity: O(n) for duplicate removal with hash set, O(n log n) for sorting, total O(n log n). Space complexity: O(n) for hash set, O(log n) for quicksort recursion. Discuss edge cases: empty array, all duplicates, already sorted, negative numbers, and zeros.
Walk through a small example to verify correctness. Consider if the array size (75) is small enough that a simpler O(n^2) algorithm might be acceptable, but still aim for optimal. Mention potential optimizations like using a boolean array if the range of values is known, but not given.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.