Start by clarifying the problem and edge cases, then present a sliding window algorithm using a hash map to track character indices. Walk through a concrete example to illustrate, argue correctness via invariants, and analyze time and space complexity.
Pro tip: Mention that the algorithm naturally handles Unicode if you treat characters as code points (e.g., using runes in Go or code points in Python) and discuss the trade-off between using a fixed-size array for ASCII versus a hash map for general Unicode.
Ask whether the string can be empty, contain all identical characters, or include Unicode. Confirm that we need both the length and an example substring.
Explain that we maintain a window [left, right) and expand right, updating the left boundary when a duplicate is found using a map from character to last index.
Choose a string like 'abcabcbb' and trace the algorithm step by step, showing how the window and max length update.
State the invariant: the window always contains no repeated characters, and we record the maximum length seen. Prove that any longer substring would have been considered.
Time O(n) with a single pass, space O(min(n, m)) where m is the alphabet size. Discuss empty string (return 0), all identical (return 1), and Unicode handling.
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