Find Subsequence of Length K With the Largest Sum
A easy-tier problem at 46% community acceptance, tagged with Array, Hash Table, Sorting. Reported in interviews at Accenture and 1 others.
You need to pick K elements from an array and maximize their sum while preserving the original order. It sounds trivial until you realize the subsequence constraint means you can't just grab the K largest values and sort them back. Accenture and Oracle both ask this. The acceptance rate sits at 45%, which tells you most candidates solve it wrong on their first attempt. If you freeze on this during a live assessment, StealthCoder surfaces a working solution invisible to the proctor.
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Find Subsequence of Length K With the 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. Made by a working Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE.
Get StealthCoderThe trap is thinking you can greedily pick the K largest numbers and rearrange them. You can't. A subsequence maintains relative order from the original array. The actual pattern: find the K largest elements (use a min-heap or sorting), then iterate through the array once and pick those elements in the order they appear. Common fail: forgetting to track which values you've already used, or trying to sort after selection. The heap approach works cleanly: build a heap of size K as you scan left-to-right, then do a second pass to extract in order. If this edge case hits you cold in the assessment, StealthCoder runs it in seconds and shows you the working code.
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Find Subsequence of Length K With the Largest Sum recycles across companies for a reason. It's easy-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 a working Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Find Subsequence of Length K With the Largest Sum interview FAQ
Why does greedy selection of K largest fail here?+
Subsequences preserve original array order. If you pick the K largest values and rearrange them, you've broken the constraint. You must find the K largest values first, then iterate the original array and collect them in the order they appear.
Is this really asked at Accenture and Oracle?+
Yes. Both companies appear in the reported data for this problem. It's a medium-difficulty logic check that screens for understanding the difference between subsequence and subarray constraints.
What's the optimal approach?+
Use a min-heap of size K to track the K largest elements as you scan the array. Once you've identified which K values to keep, do a second pass through the original array and collect them in order. Time: O(n log K), space: O(K).
How does this relate to sorting and heap topics?+
You need sorting or a heap to identify the K largest values efficiently. The heap is preferred because you only maintain K elements in memory, not a sorted copy of the entire array. Sorting the whole array then filtering also works but wastes time and space.
Why is the acceptance rate only 45%?+
Most candidates either forget the order constraint and sort the result, or implement inefficient two-pass logic. The trick is realizing you need to find the K largest first, then preserve order on the second scan. It's a pattern that requires a second read of the problem.
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