Start by clarifying the problem constraints (e.g., sorted input, duplicates, return indices or values) and then present a brute-force solution before optimizing. Use a hash map to achieve O(n) time by storing each number's complement as you iterate, and discuss trade-offs with sorting and two-pointer approaches.
Pro tip: Meta interviewers value clean, bug-free code and clear communication over clever tricks. Write the hash map solution with meaningful variable names, handle edge cases explicitly, and test with a small example to demonstrate thoroughness.
Ask about input size, sortedness, duplicates, and whether to return indices or values. Confirm expected time/space complexity.
Mention the O(n^2) nested loop approach, then propose a hash map for O(n) time and O(n) space, or sorting + two pointers for O(n log n) time and O(1) space.
Write clean code for the hash map approach: iterate through the array, check if target - num exists in the map, and return the pair. Handle edge cases like no solution.
Walk through a small example, test edge cases (empty array, no solution, duplicates), and verify time/space complexity.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.