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

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

Updated 2026-09MediumDynamic Programming

The problem at Stripe

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

Stripe uses this problem to assess apis, money, and pragmatic engineering. Expect Stripe-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 Stripe looks for

Pragmatic engineering — code that works and is maintainable.
API and product thinking — design interfaces developers love.
User empathy — Stripe cares deeply about developer experience.
Clarity in writing and communication.

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