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

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

Updated 2026-09MediumDynamic Programming

The problem at Meta

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

Meta uses this problem to assess move fast, ship impact, scale thinking. Expect Meta-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 Meta looks for

Coding speed and correctness — produce working, optimal code quickly.
Scale thinking — design for billions of users in the system design round.
Builder mindset — bias toward shipping and measuring.
Behavioral: impact, collaboration, and handling ambiguity.

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