I recognized the sliding window pattern pretty fast since it's basically the same idea as the single-string version.
Start by clarifying the problem: confirm whether to return the length or the subarray, and discuss edge cases like empty input. Then propose a sliding window with a hash set to track unique strings, achieving O(n) time and O(k) space where k is the window size. Walk through the algorithm, analyze trade-offs, and mention possible optimizations or variations.
Pro tip: Emphasize that the sliding window approach is optimal for this problem, but also discuss how you would handle very large inputs or memory constraints, showing awareness of production-scale considerations at Netflix.
Ask whether to return the length or the subarray, and confirm handling of empty input, single element, and all duplicates. This ensures alignment with the interviewer.
Explain that you'll maintain a window [left, right) and a set of strings in the window. Expand right, and if a duplicate is found, shrink from left until the duplicate is removed.
Trace the algorithm on a small example like ['a','b','a','c'] to demonstrate correctness and how the window updates.
State that time complexity is O(n) since each element is added and removed at most once, and space is O(k) where k is the maximum unique strings. Discuss alternatives like brute force O(n^2) and why sliding window is better.
Mention how to return the actual subarray by tracking start and max length, and consider memory optimizations if the alphabet is large or strings are long.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.