Classic subarray problem but I second-guessed myself on the edge cases, like what happens when all elements are negative.
Clarify the problem first: confirm whether 'maximum positive contiguous sequence' means the maximum sum of a contiguous subarray that is positive, or the longest contiguous sequence of positive numbers. Then present Kadane's algorithm for maximum subarray sum, handling all-negative arrays by returning 0 or the maximum single element as appropriate. Walk through a small example and state time and space complexity.
Pro tip: At Amazon, interviewers value candidates who proactively discuss edge cases (all negatives, zeros, single element) and can explain why Kadane's algorithm works, not just recite it. Also, mention that if the problem is about the longest run of positives, a simple linear scan suffices—showing you can disambiguate requirements is a plus.
Ask whether 'maximum positive contiguous sequence' refers to the maximum sum of a contiguous subarray that is positive, or the longest contiguous sequence of positive integers. Confirm input constraints and expected output format.
If it's maximum subarray sum, use Kadane's algorithm: iterate through the array, maintaining current sum and max sum, resetting current sum to 0 when it becomes negative. If it's longest positive run, use a simple linear scan counting consecutive positives.
Consider arrays with all negative numbers, zeros, a single element, and empty arrays. Decide on the return value (e.g., 0 for no positive sum, or the maximum element if required).
Trace the algorithm on a small array like [-2, 1, -3, 4, -1, 2, 1, -5, 4] to demonstrate correctness and show how the maximum sum is found.
State that the solution runs in O(n) time and O(1) space. Mention that this is optimal since any algorithm must examine each element at least once.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.