Clarify the problem constraints and edge cases, then propose a linear scan that tracks the current run and the best run. Discuss time and space complexity and consider if the array is sorted or if there are memory constraints.
Pro tip: Mention that if the array is sorted, the problem reduces to finding the longest run, but if not, you still need to scan all elements. Also, discuss potential follow-ups like handling streaming data or multiple queries.
Ask about input size, whether the array is sorted, and what to return if multiple subarrays have the same length. Confirm that 'subarray' means contiguous elements.
Propose a single-pass algorithm: initialize max_len and current_len to 1, then iterate from the second element, incrementing current_len if the current element equals the previous, else resetting to 1. Update max_len accordingly.
State that the time complexity is O(n) and space complexity is O(1), which is optimal for this problem.
Discuss empty array (return 0), single element (return 1), and all elements the same (return n). Also consider if the array can be modified or if it's read-only.
Walk through a small example like ['a','a','b','b','b','a'] to verify the algorithm returns 3. Mention potential off-by-one errors.
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