Minimum Genetic Mutation
A medium-tier problem at 55% community acceptance, tagged with Hash Table, String, Breadth-First Search. Reported in interviews at X and 0 others.
Minimum Genetic Mutation is a string transformation problem that looks deceptively simple until you hit the constraints. You're given a start DNA string, an end string, and a bank of valid intermediate strings. You need to find the shortest sequence of single-character mutations to get from start to end, using only strings in the bank. X has asked this one. The acceptance rate sits just above 55%, which means half the candidates who attempt it don't pass. Most failures come from treating it as a shortest-path problem without setting up the graph correctly, or over-complicating the state space. If you blank on the BFS structure during the live assessment, StealthCoder runs invisibly and hands you the working solution in seconds.
Companies that ask "Minimum Genetic Mutation"
Minimum Genetic Mutation 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 key insight is that this is a shortest-path problem on an implicit graph where each valid mutation is an edge. BFS is the natural fit: start from the initial string, explore all valid one-character mutations that exist in the bank, and track visited states to avoid cycles. The trap is managing the bank lookup efficiently. If you iterate the entire bank for every state, you'll time out. Hash the bank upfront. Another common miss: candidates forget to check whether the end string is reachable at all, or they mix up the termination condition. The algorithm is clean once you see it, but under interview pressure without prep, the setup takes time. StealthCoder handles the boilerplate and the state transitions, so you don't lose points on timing or off-by-one errors in your BFS queue.
Pattern tags
You know the problem.
Make sure you actually pass it.
Minimum Genetic Mutation 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.
Minimum Genetic Mutation interview FAQ
Why does BFS work here and not Dijkstra?+
All edges have equal weight (each mutation counts as one step), so BFS explores states in order of distance. Dijkstra is overkill and slower. BFS guarantees the shortest path in unweighted graphs and is simpler to code correctly under time pressure.
What's the trick to avoiding a timeout?+
Convert the bank to a set or hash table before the loop. If you iterate the entire bank for every mutation candidate, you'll hit O(n^2) or worse. Hashing the bank keeps lookups O(1), which keeps the overall algorithm efficient.
Is this still asked at companies like X?+
Yes. X has reported this problem. It shows up in medium-difficulty rounds and screens for BFS competence and string handling. Acceptance at 55% suggests it's not a gimme, so expect edge cases in the live assessment.
What are common failure cases I should test?+
End string not in the bank (return -1). Start equals end (return 0). Single mutation steps. Bank with no valid mutations from start. All four topics (Hash Table, String, BFS) appear in the test cases, so test both the logic and the data structure setup.
How does this relate to other graph problems?+
It's a textbook BFS template: implicit graph, state transitions, shortest path. If you've solved word-ladder or number-sequence problems, the structure is the same. Hash Table is used for fast membership checks on the bank and visited set.
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