Explain Kadane algorithm for maximum subarray sum
Reported in Apple interview loops. Frequent array optimization question testing dynamic programming intuition.
Interview scenario
Context for Apple candidates:
Find the contiguous subarray with the largest sum in a given integer array.
Model answer
Try answering aloud first
Cover trade-offs, structure, and a concrete example before revealing the baseline response.
How to frame this at Apple: Connect your answer to measurable impact, clarity of thought, and trade-offs the team cares about. Below is a strong baseline response you can adapt with your own project examples.
Kadane algorithm tracks two values while iterating: current best subarray ending at index i, and global best seen so far. At each element, decide whether to extend the previous subarray or start a new one from the current value.
The recurrence is current = max(nums[i], current + nums[i]) and best = max(best, current). This runs in O(n) time with O(1) space and is usually preferred over nested loops.
Interview tip: explicitly mention all-negative arrays, where the answer is the largest single element, not zero.
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