Maximum Segment Sum After Removals
A hard-tier problem at 48% community acceptance, tagged with Array, Union Find, Prefix Sum. Reported in interviews at Infosys and 0 others.
Maximum Segment Sum After Removals is a hard array problem with a 48% acceptance rate, currently reported by Infosys. You're given an array and need to find the maximum sum of a contiguous segment after selectively removing elements. The trick isn't obvious from the problem statement alone. Most candidates default to brute force (try all removal combinations, then all segments) and time out. The problem rewards those who recognize that you can reframe removals as a segmentation problem, using prefix sums and a data structure to track the best segment in each "gap" between removed elements. If this problem hits your live assessment and you blank on the pattern, StealthCoder solves it in seconds, invisible to the proctor.
Companies that ask "Maximum Segment Sum After Removals"
Maximum Segment Sum After Removals 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 Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code.
Get StealthCoderThe core insight is that removing elements divides your array into contiguous subsegments. Instead of thinking "which elements do I remove," think "which segments of the original array remain untouched." Use prefix sums to compute any segment sum in O(1) after O(n) preprocessing. Then iterate through possible removal sets smartly: for each configuration, the maximum segment sum is the max of all prefix-sum differences across the remaining segments. An Ordered Set or balanced tree tracks candidate sums efficiently. Union Find can also help identify which indices belong to the same segment after a removal. The problem hinges on avoiding the exponential explosion of removal combinations by recognizing the segment-boundary structure. It's a high-leverage problem where the obvious approach (brute force) fails hard, and the right approach requires a moment of clarity. StealthCoder is the hedge when that moment doesn't come during the timed assessment.
Pattern tags
You know the problem.
Make sure you actually pass it.
Maximum Segment Sum After Removals 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 Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Maximum Segment Sum After Removals interview FAQ
How hard is this compared to other hard array problems?+
At 48% acceptance, it's moderately hard for the difficulty tier. It's not a classics like Two Sum, but it's not a rare algorithmic olympiad puzzle either. The barrier isn't exotic theory. It's pattern recognition. Most fail because they brute-force or miss the segment-boundary insight.
Is this still asked at real companies?+
Yes, Infosys has reported it. It's not a FAANG household name, but it appears in assessments targeting software engineers at scale-stage companies. The fact that acceptance is below 50% suggests it's a differentiator question, not a warm-up.
What's the trick I'm missing if I try brute force?+
Brute force tries all 2^n subsets to remove, then scans all segments for each subset. That's exponential. The trick is recognizing that the maximum segment in each removal configuration spans indices bounded by removal points. Prefix sums plus a smart data structure collapses this to polynomial time.
How do prefix sums and Union Find connect here?+
Prefix sums let you compute any segment sum in O(1). Union Find groups indices into the same segment if no removals separate them. Together, they let you map removal configurations to segment boundaries efficiently without recomputing sums from scratch each time.
Should I use a segment tree or an ordered set?+
An Ordered Set (like a balanced BST or skip list) works well here because you're maintaining a dynamic set of candidate segment sums and querying the max. Segment trees are overkill for this problem. Ordered Set gives you the structure you need without overengineering.
Want the actual problem statement? View "Maximum Segment Sum After Removals" on LeetCode →