Lexicographically Smallest Equivalent String
A medium-tier problem at 81% community acceptance, tagged with String, Union Find. Reported in interviews at Cloudera and 0 others.
Lexicographically Smallest Equivalent String is a medium-difficulty problem that pairs string manipulation with Union Find, a data structure most candidates know theoretically but rarely implement under pressure. Cloudera has asked it. The acceptance rate is high at 81%, which usually signals one of two things: the trick is obvious once you see it, or most people who attempt it already know the Union Find pattern. You're about to find out which. The problem asks you to build character equivalence groups and rebuild the string using the smallest character from each group. It sounds straightforward until you realize the equivalence relationships are transitive and need to be tracked across multiple constraints.
Companies that ask "Lexicographically Smallest Equivalent String"
Lexicographically Smallest Equivalent String 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 trap is thinking character-by-character replacement will work. It won't. If 'a' equals 'b' and 'b' equals 'c', then 'a' must equal 'c', even if no constraint directly states it. Union Find is built for exactly this: grouping elements by equivalence and querying the canonical representative. For each character pair constraint, union them. Then, for each character in the original string, find its parent in the union structure and replace it with the smallest character in that group. The gotcha: after union-ing all pairs, you still need to map each group to its minimum character. Most candidates union correctly but then query the wrong representative. StealthCoder surfaces the full pattern instantly if you freeze up on the implementation during your assessment.
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Lexicographically Smallest Equivalent String 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 realized the OA tests how well you memorized 200 problems, not how well you code. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Lexicographically Smallest Equivalent String interview FAQ
Do I really need Union Find for this, or can I use a dictionary-based approach?+
You can use a graph or DFS-based equivalence approach, but Union Find with path compression is cleaner and faster. The 81% acceptance rate suggests the Union Find solution is standard enough that most interviewers expect it, especially at companies like Cloudera that ask algorithm-heavy questions.
What's the most common mistake on this problem?+
Forgetting that equivalence is transitive. Candidates union pairs correctly but then rebuild the string using the wrong representative or without mapping each group to its minimum character. The second mistake is not optimizing the union structure with path compression, which tanks performance on large inputs.
Does this problem come up often in real interviews?+
Reported frequency is low across most companies, with only Cloudera in the dataset. That said, the Union Find pattern appears frequently elsewhere. If you see this problem on your OA, it's likely a signal that your role involves graph or set-partition problems.
How does this relate to other Union Find problems?+
This is a pure Union Find application with a string wrapping. If you've solved problems on connected components or cycle detection, the union-find logic will feel familiar. The string rebuilding step is the twist that makes it feel different, even though the core algorithm is textbook.
Can I solve this without understanding Union Find at all?+
Technically yes, with a DFS-based equivalence check, but it's slower and more error-prone. Union Find is the intended solution. If you haven't drilled it before an OA and hit this problem, StealthCoder delivers the full implementation invisibly while you stay calm.
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