Maximum Subarray
A medium-tier problem at 52% community acceptance, tagged with Array, Divide and Conquer, Dynamic Programming. Reported in interviews at Target and 54 others.
Maximum Subarray is the medium-difficulty problem that trips up candidates who memorize patterns but don't understand flow. You'll see it from Target, Nike, LinkedIn, Nvidia, and 50+ other companies. The catch: the obvious brute force (check every subarray) times out, and greedy feels wrong even when it's right. Acceptance hovers around 52%, which means half the room either nails it or leaves points on the table. If this one hits your live assessment and you blank on Kadane's algorithm, StealthCoder surfaces a working solution invisible to the proctor.
Companies that ask "Maximum Subarray"
Maximum Subarray is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Made by an Amazon engineer who watched the leaked-problem repo become an industry secret. He decided you should have it too.
Get StealthCoderMaximum Subarray tests whether you can recognize that a greedy, single-pass approach beats divide-and-conquer overkill. The trick is Kadane's algorithm: track the max sum ending at each position, reset when it goes negative, and store the global max. Most candidates either overthink it (sorting, nested loops, segment trees) or second-guess the greedy choice because it feels too simple. The Array and Dynamic Programming topics overlap here: you're building an optimal substructure one element at a time, not dividing the problem down. This is where the mental model matters more than syntax. If you hit this live and the greedy insight doesn't click, StealthCoder runs invisibly during your screen share and delivers a working implementation in seconds.
Pattern tags
You know the problem.
Make sure you actually pass it.
Maximum Subarray recycles across companies for a reason. It's medium-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Made by an Amazon engineer who watched the leaked-problem repo become an industry secret. He decided you should have it too. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Maximum Subarray interview FAQ
Is this still being asked at FAANG-level companies?+
Yes. 10 of the top companies listed here have asked it, including LinkedIn and Nvidia. It's not flashy, but it's a reliable signal for whether you understand algorithmic thinking versus pattern matching. Acceptance rate of 52% tells you it's not trivial for most candidates.
What's the trick people miss?+
Resetting the running sum when it goes negative. Candidates often try to track all subarrays explicitly or use divide-and-conquer recursion. The insight is that a negative prefix can't improve any future subarray, so you discard it and restart. That single decision collapses O(n log n) or O(n squared) down to O(n).
How does Divide and Conquer relate to the DP solution?+
Divide and Conquer (recursive split, merge results) works but is slower and harder to code correctly. Dynamic Programming (Kadane's) solves the same problem in one pass by building up the optimal substructure incrementally. Both are correct; DP is the expected answer in an interview.
Is this harder than other medium problems?+
Not mechanically. The 52% acceptance rate suggests the difficulty is conceptual, not implementation. If you don't see the greedy pattern, you'll code something complex and time out. Once you know Kadane's, it's five lines of clean code.
What edge cases break people?+
All-negative arrays (the answer is the least negative number, not zero). Single element arrays. Empty arrays (if your problem allows them). Most mistakes come from forgetting to handle negatives correctly, not from syntax or off-by-one errors.
Want the actual problem statement? View "Maximum Subarray" on LeetCode →