Knew the sliding window approach going in, which helped.
Use a sliding window with a hash map to track the last seen index of each character, expanding the right pointer and moving the left pointer when a duplicate is found. This yields O(n) time and O(min(n, alphabet)) space, which is optimal for this problem.
Pro tip: Clarify assumptions upfront (e.g., character set, empty string, case sensitivity) and mention that the sliding window approach is preferred over brute force for scalability. Also, discuss how you would handle Unicode characters if relevant.
Ask about the character set (ASCII, Unicode), empty string, and whether the substring must be contiguous. Confirm that we need the length, not the substring itself.
Explain that we maintain a window [left, right] with unique characters, using a hash map to store the last index of each character. When a duplicate is encountered, move left to max(left, lastIndex[char] + 1).
Trace the algorithm on a sample string like 'abcabcbb' to demonstrate how the window expands and contracts, and how the maximum length is updated.
State that time complexity is O(n) since each character is visited at most twice, and space is O(min(n, m)) where m is the alphabet size. Mention that using an array instead of a hash map can optimize for ASCII.
Be prepared to handle variations like allowing at most k distinct characters or finding the longest substring with at most two distinct characters, which use similar sliding window techniques.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.