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

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

Updated 2026-09MediumDynamic Programming

The problem at Google

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

Google uses this problem to assess algorithmic rigor and generalist problem-solving. Expect Google-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 Google looks for

Algorithmic fluency — the right data structure and the optimal complexity, fast.
Googleyness — comfort with ambiguity, intellectual curiosity, and a collaborative style.
Leadership and impact — especially at L4+; evidence of driving outcomes.
Communication — explaining your thinking as you solve.

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