Largest Number After Mutating Substring
A medium-tier problem at 37% community acceptance, tagged with Array, String, Greedy. Reported in interviews at Infosys and 0 others.
Largest Number After Mutating Substring is a medium-difficulty problem that asks you to maximize a numeric string by selectively transforming a contiguous substring. The catch: you can only mutate one substring, and the rule for what counts as a valid mutation is the stumbling block most candidates hit. With a 37% acceptance rate, this problem filters out people who brute-force without thinking. Infosys has asked it. If this problem lands in your OA and you're not certain about the greedy strategy, StealthCoder runs invisibly during screen share and surfaces a working solution in seconds.
Companies that ask "Largest Number After Mutating Substring"
Largest Number After Mutating Substring 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. Made for the engineer who has done the work but might still blank with a webcam pointed at him.
Get StealthCoderThe core trick is greedy selection. You need to pick which substring to mutate such that the resulting number is maximum. The obvious approach, try all substrings, works but is slow if you don't optimize. The real insight is recognizing that not every mutation helps. You want to mutate digits in a way that pushes larger values leftward, because positional weight matters in numeric comparison. Many candidates waste time writing brute-force code without realizing the pattern: you're looking for the leftmost position where mutation yields gain, and you stop as soon as continuing mutation would lose value. This is an Array and String problem that demands Greedy thinking. StealthCoder bridges the gap if you freeze on the optimization during the live assessment.
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Largest Number After Mutating Substring 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. Made for the engineer who has done the work but might still blank with a webcam pointed at him. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Largest Number After Mutating Substring interview FAQ
What does 'mutating a substring' actually mean here?+
You pick a contiguous range of indices and apply a transformation rule to those digits. The exact rule is given in the problem statement. The key is understanding that mutation isn't free; you must choose one substring, so picking the right span is the entire puzzle.
Is this problem still asked at top companies?+
Infosys has reported asking it. Lower frequency overall based on available data, but it's exactly the kind of problem that shows up in assessment rotations. If you see it, prepare to explain your greedy choice.
Why is the acceptance rate so low at 37%?+
Most candidates either brute-force without optimization or miss the greedy insight entirely. The problem looks simple on the surface but punishes inefficient thinking. Understanding why certain mutations are never worth it is the gate.
How does this relate to the Greedy topic?+
Greedy means you pick the locally optimal choice at each step, in this case, mutating the substring that gives you the maximum result, without backtracking. You evaluate candidates in order and commit to the best one.
Should I try all substrings or optimize first?+
Start with clarity on the brute-force: O(n squared) substrings, O(n) work per substring. Then ask yourself: can I prune early? Can I skip clearly bad substrings? That pruning step is often where the insight clicks.
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