Lexicographically Smallest String After Applying Operations
A medium-tier problem at 65% community acceptance, tagged with String, Depth-First Search, Breadth-First Search. Reported in interviews at J.P. Morgan and 0 others.
You're handed a string and a set of operations that transform it. The problem asks for the lexicographically smallest result after applying operations optimally. J.P. Morgan has asked this. The trap is obvious: brute force all permutations or greedy choices fail because the order matters and distant states can produce smaller results. You need to explore the state space intelligently, using either DFS or BFS to find the global minimum without getting stuck in local optima. If this lands in your live OA and you freeze on the traversal strategy, StealthCoder solves it invisibly in seconds.
Companies that ask "Lexicographically Smallest String After Applying Operations"
Lexicographically Smallest String After Applying Operations 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 core trick is recognizing this as a graph search problem, not a string manipulation one. Each string state is a node, and each operation creates an edge. From any state, you can apply operations in any order to reach new states. Greedy (always pick the lexicographically smallest immediate result) doesn't work because you might need to make a 'worse' move to unlock a better final state. DFS with memoization or BFS across all reachable states will find the answer, but you must prune carefully to avoid exponential blowup. The 'Enumeration' topic hints that you're exploring combinations of operations, not optimizing a single path. Most candidates start greedy, hit a failing test case, then realize they need full state-space search. StealthCoder hedges that moment during the assessment.
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Lexicographically Smallest String After Applying Operations 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.
Lexicographically Smallest String After Applying Operations interview FAQ
Is this really just greedy?+
No. Greedy fails because the lexicographically smallest immediate move doesn't guarantee the smallest final string. You may need to apply operations in a non-greedy order to unlock better states. You need DFS or BFS to explore the full reachable state space.
How do I avoid exploring infinite states?+
Use a visited set to track which strings you've already processed. Once you've explored a state, you don't revisit it. This turns the problem from exponential enumeration into a bounded graph traversal. Memoization is your friend.
What's the difference between DFS and BFS here?+
Both work. DFS with memoization is memory-efficient for deep trees. BFS guarantees shortest operation sequences first, which can be cleaner to reason about. Pick whichever you're more comfortable coding under pressure.
How hard is this problem really?+
Medium difficulty is fair. The conceptual leap (recognizing it's state-space search, not greedy) is the hardest part. Once you see that, the implementation is straightforward DFS or BFS with a visited set. Acceptance rate of 65% reflects that many candidates miss the pattern initially.
Will J.P. Morgan ask follow-ups after I solve it?+
Likely. Be ready to discuss time complexity of your state-space search, whether you can optimize the visited set, and how the number of operations affects the answer space. Understanding why greedy fails is the key insight they probe.
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