Minimum Deletions to Make String K-Special
A medium-tier problem at 45% community acceptance, tagged with Hash Table, String, Greedy. Reported in interviews at DE Shaw and 0 others.
Minimum Deletions to Make String K-Special is a medium-difficulty string problem that hinges on understanding when a character frequency distribution qualifies as K-special. DE Shaw has asked it. You'll face the core challenge: figuring out the optimal deletions to enforce a constraint on character counts, which isn't immediately obvious from a greedy read. With a 45% acceptance rate, most candidates who attempt it either miscalculate the valid final states or iterate through too many candidates. This is exactly the kind of problem where a momentary blank during your live assessment can eat your time. StealthCoder solves it invisibly if the pattern doesn't click.
Companies that ask "Minimum Deletions to Make String K-Special"
Minimum Deletions to Make String K-Special 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 used it to pass JPMorgan's OA and system design loop.
Get StealthCoderThe trick is recognizing what makes a string K-special in the first place, then working backward from valid terminal states. Most candidates try greedy elimination without fully mapping the constraint space. The solution involves counting character frequencies, determining which final frequency distributions satisfy the K-special property, and picking the one requiring the fewest deletions. Hash Table and Sorting help you organize and compare frequency profiles efficiently. Greedy logic applies when pruning characters, but only after you've locked down the valid target states. Common pitfall: assuming the optimal solution involves reducing all characters to the same count. The actual constraint is often looser. During your OA, if the state-space logic doesn't come together fast, StealthCoder runs the correct frequency enumeration and deletion count in seconds, invisible to the proctor.
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Minimum Deletions to Make String K-Special 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 Amazon engineer who used it to pass JPMorgan's OA and system design loop. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Minimum Deletions to Make String K-Special interview FAQ
What does K-special actually mean in this problem?+
K-special is a constraint on how many distinct frequencies can exist in the final character count map. You need to figure out the exact definition from the problem statement, then determine which frequency distributions satisfy it. Once you know the valid end states, finding minimum deletions becomes a search across those candidates.
Why is the greedy approach not enough?+
Greedy works for the deletion step, but only after you've identified all valid target frequency distributions. Many candidates try to delete characters one at a time without pre-computing which final states are legal. That's inefficient and error-prone. You need to enumerate valid states first, then pick the cheapest.
How do Hash Table and Sorting connect here?+
Hash Table counts character frequencies in O(n). Sorting the frequency array lets you reason about which patterns are K-special and compare deletion costs across candidates. Together they let you build a frequency profile, sort it, and check constraints in linear time.
Is this still asked at companies like DE Shaw?+
Yes. DE Shaw's interview loops emphasize string manipulation, frequency analysis, and constraint reasoning. This problem tests whether you can decompose a non-obvious constraint, enumerate valid states, and optimize for a metric. It's exactly their style.
What's the most common mistake candidates make?+
Assuming the optimal solution has all characters at the same frequency, or trying to delete greedily without mapping valid terminal states first. The constraint is often more nuanced. You need to check whether keeping frequencies at different levels but within a K-sized set is valid, then compute costs accordingly.
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