Min Moves
Reported by candidates from Google's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
Google's Min Moves question hit your cohort in September, and it's a straightforward optimization problem that catches candidates off guard because the naive approach feels right. You're looking at a state-space search where the trick is recognizing which moves actually matter and which are wasted effort. The pattern is greedy or BFS depending on the exact constraints, but either way you need to see the shortcut before you code. StealthCoder reads the exact problem constraints on your screen and surfaces the optimal approach in real time, so you're never stuck between two strategies during the live assessment.
Pattern and pitfall
Min Moves problems typically boil down to finding the minimum number of operations to reach a target state from an initial state. The common pitfall is simulating every possible move, which tanks your time complexity. What actually works is recognizing that certain moves are always suboptimal and pruning them, or using BFS to explore only reachable states level by level. Google tends to hide the trick in the problem statement: often there's a mathematical shortcut that eliminates entire branches of the search tree. If the problem involves transforming a number or array, check whether greedy swaps or reordering always beats the next-move-only approach. When you're live and your first instinct feels too slow, that's when you need the safety net. StealthCoder surfaces the pattern immediately so you can code the efficient version without second-guessing.
If you see this problem in your OA tomorrow, the play is to recognize the pattern in 30 seconds. StealthCoder buys you that recognition.
You can drill Min Moves cold, or you can hedge it. StealthCoder runs invisibly during screen share and surfaces a working solution in under 2 seconds. The proctor sees the IDE. They don't see what's behind it. Built by an Amazon engineer who passed his OA cold and still thinks the filter is broken.
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Google reuses patterns across OAs. Built by an Amazon engineer who passed his OA cold and still thinks the filter is broken. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Min Moves FAQ
Is this a BFS problem or can I solve it greedily?+
It depends on the exact constraint. If all moves have equal cost and you need the absolute minimum count, BFS is safer. If you can prove a greedy choice is always optimal (like always picking the largest gap to close first), go greedy. Read the problem carefully for hints about structure before you pick your tool.
What's the most common mistake candidates make on Min Moves?+
Simulating every move without pruning, or overlooking a mathematical shortcut that makes the problem trivial. Google loves hiding the trick in plain sight. Look for patterns like 'this operation is always reversible' or 'these two moves commute' before you code.
How do I prepare in 48 hours if I'm weak on optimization?+
Solve two or three classic problems: coin change (DP greedy hybrid), jump game (greedy), and word ladder (BFS). Don't memorize solutions. Instead, practice spotting when to prune, when to use greedy, and when BFS is the only safe bet. Pattern recognition matters more than speed.
Will the test case constraints hint at the algorithm?+
Almost always. If N is up to 10^5, BFS with pruning works. If N is up to 10^6 or 10^9, you need a mathematical insight or greedy choice. Check the examples too: if moving in one direction is always better, that's your greedy signal.
What if I blank on the optimal approach during the OA?+
Write a brute-force BFS solution that explores all moves but stops early when you hit the target. It'll be slow but correct. Then optimize if you have time. StealthCoder can also surface the pattern if you're truly stuck and need a hint.