First, clarify the discrepancy between the problem label and the actual requirement, confirming that the expected output is the union of unique elements. Then, propose an efficient solution using a hash set to collect unique elements from both arrays, and discuss time and space complexity. Finally, walk through an example to demonstrate correctness.
Pro tip: Mention that in real-world scenarios, ambiguous problem statements are common, so it's crucial to confirm requirements with stakeholders before coding. Also, note that using a hash set is optimal for average-case O(n+m) time, but if the arrays are sorted, a two-pointer approach could be more space-efficient.
Point out the mismatch between the label 'intersection' and the described output 'union', and ask the interviewer to confirm the expected behavior.
Propose using a hash set to store unique elements from both arrays, then convert to an array. Mention alternative approaches like sorting and two pointers if the arrays are already sorted.
State that the hash set approach runs in O(n+m) average time and O(n+m) space, while the two-pointer approach on sorted arrays uses O(1) extra space but O(n log n + m log m) time if sorting is needed.
Write clean code for the chosen approach, handling edge cases like empty arrays or duplicates. Walk through a small example to verify correctness.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.