I recognized it as a sliding window problem pretty fast, which helped.
Start by clarifying the problem and edge cases, then propose an efficient sliding window solution using a hash map to track the last seen index of each element. Walk through the algorithm with a small example, analyze time and space complexity, and discuss how to optionally return the subarray itself.
Pro tip: Emphasize that the sliding window approach achieves O(n) time by avoiding redundant checks, and mention that using a hash map to store the last seen index allows the left pointer to jump directly, which is more efficient than a set-based approach that removes elements one by one.
Ask whether the input can be empty, contain nulls, or have mixed types, and confirm if the subarray itself is needed or just its length. Discuss how to handle these cases.
Explain the sliding window technique with a hash map to track the last index of each element, maintaining a window of distinct elements. Describe how to update the left pointer when a duplicate is found.
Trace the algorithm on a small input, such as [1, 2, 1, 3, 2], showing how the window expands and contracts, and how the maximum length is updated.
State that the time complexity is O(n) because each element is processed at most twice, and space complexity is O(min(n, m)) where m is the number of distinct elements.
If required, explain how to track the start and end indices of the longest window and return the subarray using slicing.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.