Length of the Longest Subsequence That Sums to Target
A medium-tier problem at 37% community acceptance, tagged with Array, Dynamic Programming. Reported in interviews at Intuit and 0 others.
You're staring at a medium DP problem that only 37% of candidates pass on first attempt. The trick isn't obvious, and that's by design. Intuit has asked this one, and it'll show up in your OA if you're unlucky enough to draw medium difficulty. The problem looks like a subset sum variant, but the subsequence angle changes everything. Most candidates either brute-force combinations (timeout) or confuse subsequence with subarray and tank their logic. If you blank on the state transitions during the live assessment, StealthCoder runs invisibly and surfaces a working solution in seconds.
Companies that ask "Length of the Longest Subsequence That Sums to Target"
Length of the Longest Subsequence That Sums to Target 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 who got tired of watching his cohort grind for six months and still get filtered at the OA stage.
Get StealthCoderThe core insight is that you're not looking for contiguous elements, you're picking any elements from the array in order while maintaining their relative sequence. Standard dynamic programming applies: build a 2D table where dp[i][j] represents whether you can form sum j using the first i elements. The trap is thinking you need to track which subsequence you picked, when really you just need a boolean or count. The obvious greedy approach fails because you might skip a large number early to hit your target with smaller numbers later. The real bottleneck is space and time complexity when the target is large, but the DP table size stays manageable for most interview constraints. When this hits your OA and the examples aren't clicking, StealthCoder surfaces the transition logic and avoids the off-by-one errors that sink half the submissions.
Pattern tags
You know the problem.
Make sure you actually pass it.
Length of the Longest Subsequence That Sums to Target 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. Built by an engineer who got tired of watching his cohort grind for six months and still get filtered at the OA stage. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Length of the Longest Subsequence That Sums to Target interview FAQ
How is this different from subset sum?+
Subset sum doesn't care about order, subsequence does. You must preserve the relative positions of selected elements as they appear in the array. This forces a linear scan through elements in the DP table and prevents certain optimization tricks. The DP table structure is similar, but the iteration order matters more.
Is this really asked at companies like Intuit?+
Yes. It's in their reported OA rotation. It's medium difficulty, which means it's a screening filter, not a gimme. A 37% acceptance rate confirms most candidates either miss the DP formulation or hit time limits. Intuit and similar companies use it to separate solid DP candidates from those who can't translate a word problem into state.
What's the most common mistake?+
Confusing subsequence with subarray and using a 1D DP array that doesn't track position properly. Candidates also overwrite values in place and lose information needed for later sums. Another trap is trying to reconstruct the actual subsequence when the problem only asks for existence or count. That adds complexity and introduces bugs.
Do I need to return the subsequence or just a boolean?+
Check the problem statement carefully. Most variants ask for a count or a boolean. If they ask for the actual subsequence, you'll need to backtrack through the DP table, which doubles the code length and error surface. The acceptance rate here suggests many candidates overengineer this part.
How does this relate to the knapsack?+
Both use 2D DP with similar table structure. The difference is that knapsack cares about weight and value, this only cares about hitting a target sum. The subsequence constraint is the key difference from a standard 0/1 knapsack. Understanding one makes the other click faster, so if knapsack is solid, this is a natural step up in complexity.
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