Closest Subsequence Sum
A hard-tier problem at 42% community acceptance, tagged with Array, Two Pointers, Dynamic Programming. Reported in interviews at Sprinklr and 1 others.
Closest Subsequence Sum is a hard array problem asking you to find a subsequence whose sum comes closest to zero. It shows up in technical rounds at Sprinklr and LTI. The 41% acceptance rate signals a real trick most candidates miss on first approach. The naive path (generate all 2^n subsequences) fails hard on larger inputs. You need to either split the array and use meet-in-the-middle, or compress the state space with bitmask DP. If this problem hits your live assessment and you blank on the pattern, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Closest Subsequence Sum"
Closest Subsequence 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 Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code.
Get StealthCoderThe core trap is thinking you can brute-force or greedily pick elements. Neither works. The real solution splits the input array in half, generates all possible sums from each half, then uses two pointers or a sorted structure to find the pair of sums closest to zero. This meet-in-the-middle technique drops exponential time to manageable. Alternatively, bitmask DP with sorting and pruning works if constraints allow. Most failures come from either not recognizing the need to compress the search space, or implementing the two-pointer merge incorrectly. StealthCoder's hedge here is crucial: the algorithm demands careful state design, and a live blank often means a complete rewrite under time pressure.
Pattern tags
You know the problem.
Make sure you actually pass it.
Closest Subsequence 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 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.
Closest Subsequence Sum interview FAQ
Is this really asked at Sprinklr and LTI?+
Yes. It appears in the reported interview sets for both companies. The 2-company footprint is smaller than FAANG staples, so it's less drilled in generic prep. That makes it a risky blind spot during an OA.
Why does the 41% acceptance rate matter?+
Hard problems usually sit 20-35% acceptance. 41% suggests it's hard but not broken. The candidates who pass either pre-drilled it or spotted the meet-in-the-middle pattern fast. Cold approach under time pressure is brutal.
What's the actual trick?+
Split the array, generate all subset sums from each half (O(2^(n/2)) per half), sort one half, then use two pointers to find the pair closest to zero. Bitmask or recursive enumeration works too if you prune aggressively. Brute all 2^n subsequences will timeout.
How does this relate to the Dynamic Programming topic?+
You can solve it with DP by building a set of reachable sums, but that's slower than meet-in-the-middle for moderate n. DP shines when you need all sums. Here, target is one specific value (closest to zero), so divide-and-conquer is tighter.
What if I freeze up on this during an OA?+
That's exactly where StealthCoder works. It reads the problem, sees your input, and feeds you the solution in real time. You type it, submit, move on. No proctor visibility. The hedge matters because this problem isn't intuitive and time pressure kills half the candidates.
Want the actual problem statement? View "Closest Subsequence Sum" on LeetCode →