My first instinct was a simple counter scan, which felt right until the interviewer pointed out I wasn't handling character exhaustion.
Clarify the problem requirements and edge cases, then propose a two-pass solution using frequency counting to handle duplicates correctly. Discuss trade-offs between time and space complexity, and consider follow-up optimizations like early termination or streaming for large inputs.
Pro tip: Mention that this is essentially the Wordle feedback algorithm, and highlight the importance of handling duplicate characters correctly—a common pitfall. Also, discuss how you would test your solution with edge cases like empty strings or all matching characters.
Ask about input constraints (e.g., string lengths, character set), output format (e.g., array of enums or integers), and edge cases like empty strings or case sensitivity.
First pass: mark exact matches and count remaining characters in the target. Second pass: for non-exact matches, check if the character is available in the remaining count to mark as 'present' or 'absent'.
Discuss time complexity O(n) and space complexity O(1) if using fixed-size arrays for character counts, or O(k) for hash map. Mention alternative approaches like sorting or using a hash map and their trade-offs.
Explain how the frequency count ensures duplicates are handled correctly, and walk through an example with repeated characters to demonstrate.
Mention possible optimizations like early termination if all characters match, or adapting the solution for streaming input or large datasets.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.