Start by clarifying the problem and edge cases, then propose a sliding window approach using a hash map to track the last seen index of each character. Walk through the algorithm with a small example, analyze time and space complexity, and discuss potential optimizations or alternative approaches.
Pro tip: At Amazon, interviewers value candidates who proactively discuss trade-offs and edge cases. Mention how your solution handles empty strings, all unique characters, and all identical characters, and consider if the input can contain Unicode characters.
Ask clarifying questions: What characters are allowed? Can the string be empty? Is the substring contiguous? What should be returned if no such substring exists?
Acknowledge that a brute force solution would check all substrings, but propose an optimal O(n) sliding window approach using a hash map to store the last index of each character.
Describe maintaining a window [left, right] and expanding right. If the current character is in the map and its last index >= left, update left to last index + 1. Update the map and track the maximum length.
Use a string like 'abcabcbb' to demonstrate how the window moves and how the maximum length is updated. Show the state of the map and window at each step.
State that time complexity is O(n) since each character is processed once, and space complexity is O(min(n, m)) where m is the character set size. Discuss edge cases like empty string, single character, and all unique characters.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.