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Maximum Subarray (Kadane's Algorithm) at Apple — Interview Guide

How to approach Maximum Subarray (Kadane's Algorithm) in a Apple interview: the optimal approach, what Apple interviewers look for, and company-specific tips.

Updated 2026-09MediumDynamic Programming

The problem at Apple

Given an integer array, find the contiguous subarray with the largest sum and return that sum.

Apple uses this problem to assess craft, detail, and domain depth. Expect Apple-specific follow-ups that tie the solution back to production reasoning and the company's engineering bar.

Key concepts

Kadane: at each index, the best subarray ending here is either the element alone or the element plus the best ending at the previous index.
Track the running sum, reset to 0 when it goes negative, and keep the global maximum.
Divide-and-conquer gives O(n log n) and generalizes to 2D problems.

Approach

def max_subarray(nums):
    best = cur = nums[0]
    for x in nums[1:]:
        cur = max(x, cur + x)
        best = max(best, cur)
    return best

What Apple looks for

Domain expertise relevant to the team.
Craft — performance, edge cases, and polish.
Passion for the product and user experience.
Independence and ownership of a feature end-to-end.

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