Minimize Deviation in Array
A hard-tier problem at 54% community acceptance, tagged with Array, Greedy, Heap (Priority Queue). Reported in interviews at Samsung and 0 others.
You're looking at a hard-rated problem that hits different when you're live. The trick isn't obvious from the problem statement, and candidates often start coding a brute force that times out. Minimize Deviation in Array appears in assessments for companies like Samsung and demands you understand when greedy works and when it doesn't. Most people see the numbers and think sorting or two pointers. Wrong. The real insight is that you need to track the minimum deviation across all possible states of the array, and there's a finite number of them. If this problem lands on your OA and you freeze, StealthCoder surfaces the heap-based solution in seconds, invisible to the proctor.
Companies that ask "Minimize Deviation in Array"
Minimize Deviation in Array 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 core trick: you can't just sort and compute. The array elements change based on operations (divide by 2 if even, multiply by 2 if odd), and you need to find the state that minimizes max minus min. The greedy angle is that once you've applied all possible multiplications to odd numbers, you only need to divide even numbers down. Use a max heap to track the current maximum, a set to detect duplicates and prune, and iterate by repeatedly dividing the largest element until it becomes odd. Track the deviation at each step. The trap is thinking you need to explore all branches, which explodes the state space. The correct framing is that you're greedily reducing the maximum while the minimum stays fixed, and there are only O(log max-value) divisions to try. If heap and ordered set aren't in your muscle memory, this problem will hurt on a timer.
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Minimize Deviation in Array 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.
Minimize Deviation in Array interview FAQ
Is this problem really as hard as the difficulty tag suggests?+
Yes. The acceptance rate is roughly 54%, which is lower than typical medium problems. The trick isn't algorithmic complexity, it's recognizing that you need to frame the problem as a search through finite operations, not a traditional optimization. Without that reframing, you'll timeout.
Do I need to know the greedy insight before attempting it?+
Not necessarily, but it helps immensely. The greedy move is to always divide the maximum element if it's even. The insight is that once all odd numbers are multiplied to their target, you stop multiplying and only divide. Many candidates discover this during the problem, but time pressure makes that dangerous.
What's the most common mistake on this problem?+
Trying to generate all possible arrays by applying all operations, then comparing. This explodes exponentially. The correct approach limits operations: multiply odd numbers once, then only divide. Tracking state with a heap and set keeps memory and time linear in the number of divisions.
Why does this use a heap and an ordered set?+
The heap efficiently tracks the maximum element as you divide. The ordered set (or hash set) tracks visited states to avoid reprocessing the same array configuration. Together they prune the search space and ensure you don't loop infinitely on states you've already computed.
Is this problem asked at other companies besides Samsung?+
Samsung is the only company listed in reports for this problem. It's a niche hard-rated question, so it may appear in other interviews, but data here is sparse. Treat it as a high-value edge-case problem for Samsung specifically.
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