Minimum Reverse Operations
A hard-tier problem at 15% community acceptance, tagged with Array, Breadth-First Search, Ordered Set. Reported in interviews at Infosys and 0 others.
Minimum Reverse Operations is a hard array problem with a 15% acceptance rate, asked at Infosys. You'll face a grid where you reverse subarrays of fixed length and need to find the minimum operations to reach a target state. Most candidates blank on the state-space structure and waste time on greedy or dynamic-programming approaches that don't scale. If this problem hits your live assessment and the pattern isn't immediately clear, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Minimum Reverse Operations"
Minimum Reverse 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. Made by a working FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know.
Get StealthCoderThe trick is recognizing this as a shortest-path problem, not an array transformation puzzle. You model each array state as a node and build a graph where edges represent valid reverse operations. Breadth-First Search then finds the minimum operations from start to goal. The catch: the state space explodes if you're not careful. Most candidates try to simulate reversals naively and time out. You need an Ordered Set to efficiently track which indices you can reach after k operations, pruning impossible states before they bloat your queue. This combines Array mechanics, BFS traversal, and set-based optimization into a single tight solution. StealthCoder hedges you if the BFS-plus-ordering insight doesn't click under time pressure.
Pattern tags
You know the problem.
Make sure you actually pass it.
Minimum Reverse Operations recycles across companies for a reason. It's hard-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 by a working FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Minimum Reverse Operations interview FAQ
Is this really a BFS problem or am I overthinking it?+
Yes, it is. The problem asks for minimum operations, which screams shortest path. State space is each array permutation reachable by one reverse op. Greedy fails because reversing one subarray blocks or enables others unpredictably. BFS is the canonical approach.
Why do so many solutions time out on this?+
They generate all possible next states without filtering. With n elements and reverse length k, that's exponential branching. You must use an Ordered Set to calculate reachable indices mathematically, not enumerate all reversals. This cuts the search tree dramatically.
What's the role of the reverse length constraint?+
It defines which subarrays you can flip. Only subarrays of that exact length are valid. This constraint actually helps prune the search space, but only if you pre-compute valid start positions and use set operations to track reachable indices per level.
How does Ordered Set fit into the solution?+
After each BFS level, you track which indices are reachable. Ordered Set lets you find gaps and valid ranges in O(log n) per query, avoiding redundant state generation. It's the performance lever that keeps the algorithm polynomial.
Is this asked outside Infosys and worth drilling?+
Only one company is on record asking it. That said, the BFS-plus-set-optimization pattern appears in other hard graph and state-space problems. If you're targeting Infosys or studying advanced array problems, it's worth one deep session.
Want the actual problem statement? View "Minimum Reverse Operations" on LeetCode →