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The base version is fine, just count runs since the array is sorted.
First, present the classic Boyer-Moore majority vote algorithm extended to find up to two candidates, then verify their counts in a second pass. For the optimization, leverage the sorted property to binary search for the first and last occurrence of each candidate, or directly check the elements at indices n/3 and 2n/3 to identify potential majority elements.
Pro tip: Emphasize that the sorted array allows you to find candidates by checking the elements at positions floor(n/3) and floor(2n/3), since any element appearing more than n/3 times must cross these boundaries. This insight leads to an O(log n) solution using binary search.
Confirm that the array is sorted, n >= 3, and that we need distinct values in increasing order. Discuss edge cases like multiple elements exceeding n/3 (at most two).
Explain the Boyer-Moore majority vote algorithm generalized to two candidates: first pass to find candidates, second pass to verify counts. Mention that it runs in O(n) time and O(1) space.
Describe how to use binary search to find the first and last occurrence of each candidate, or directly check elements at indices n/3 and 2n/3. This reduces time to O(log n) while keeping space O(1).
Compare the O(n) and O(log n) solutions, noting that the optimized solution relies on the array being sorted and may have higher constant factors but better asymptotic time.
Walk through a few examples, such as [1,2,3,3,3] and [1,1,2,2,3,3], to demonstrate correctness and edge cases.
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