Split Array Largest Sum
A hard-tier problem at 58% community acceptance, tagged with Array, Binary Search, Dynamic Programming. Reported in interviews at Baidu and 11 others.
Split Array Largest Sum shows up in live assessments at Microsoft, Salesforce, DE Shaw, and Pinterest. It's a hard problem with a 58% acceptance rate, which means roughly half the candidates who sit down with it either time out or lock into the wrong approach. You've got an array and need to split it into k subarrays such that the maximum sum across all subarrays is minimized. The trick isn't obvious on first read. If this problem hits your OA and you blank on the pattern, StealthCoder surfaces a working solution invisibly while you're screen-sharing, buying you time to move on.
Companies that ask "Split Array Largest Sum"
Split Array Largest Sum 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. Built by an engineer at a top-10 tech company who can solve these problems cold but didn't want to trust himself in a 90-minute screen share.
Get StealthCoderThe trap is dynamic programming. Most candidates chase a DP table and burn 20 minutes going nowhere. The real solution pairs binary search with a greedy validation function. You binary search the answer space (the max sum), and for each candidate answer, greedily check if you can split the array into k subarrays where no subarray exceeds that max. The pattern connects Array, Binary Search, and Greedy thinking. Prefix Sum helps you validate splits in constant time. This is the kind of problem where the approach matters more than the code. If you freeze on the trick in a live assessment, StealthCoder bypasses the panic and shows you the binary search frame plus the greedy checker, letting you move forward.
Pattern tags
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Split Array Largest Sum recycles across companies for a reason. It's hard-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. Built by an engineer at a top-10 tech company who can solve these problems cold but didn't want to trust himself in a 90-minute screen share. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Split Array Largest Sum interview FAQ
Is this problem really asked at FAANG?+
Yes. Microsoft, Salesforce, DE Shaw, and Pinterest all report asking it. It's not the most frequent, but it appears consistently enough that it's worth studying if those companies are on your target list.
What's the main trick I'm missing if I go DP?+
DP scales quadratically or worse in state space and time. Binary search on the answer (the max sum) and greedily validate splits instead. That's the insight that separates solvers from those who time out.
How does Prefix Sum fit in?+
During greedy validation, you need to quickly check if adding the next element to a subarray exceeds your candidate max sum. Prefix sums let you compute subarray sums in O(1). Without them, validation becomes expensive.
Why is this rated hard if the final code is short?+
Hard rating reflects the leap from DP thinking to binary search on the answer. The algorithm itself is clean, but seeing that frame under pressure is where most candidates stumble.
How much time should I spend on this before an OA?+
If you're targeting Microsoft or Salesforce, drill the binary search plus greedy validation pattern once so you recognize it. Then move on. Mastering the frame takes 30 to 45 minutes. Don't over-optimize.
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