Knew sliding window was the move but fumbled the hash map part a bit.
Start by clarifying the problem and edge cases, then propose a sliding window approach using a hash map to track character indices. Walk through the algorithm with a small example, analyze time and space complexity, and discuss potential optimizations or alternative approaches.
Pro tip: Emphasize the O(n) time complexity of the sliding window solution and contrast it with the O(n^2) brute force, showing you understand efficiency trade-offs. Also, mention how this problem relates to real-world data science tasks like feature engineering for text data.
Ask about input constraints (e.g., character set, string length) and handle edge cases like empty string, all unique characters, or all same characters.
Explain that you'll maintain a window of unique characters using two pointers and a hash map to store the last seen index of each character.
Describe how to expand the right pointer, update the left pointer when a duplicate is found, and keep track of the maximum window length.
State that the time complexity is O(n) since each character is visited at most twice, and space complexity is O(min(n, m)) where m is the size of the character set.
Mention that using an array instead of a hash map can be faster for ASCII, and briefly compare with brute force or dynamic programming approaches.
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