Minimum Number of Increments on Subarrays to Form a Target Array
A hard-tier problem at 72% community acceptance, tagged with Array, Dynamic Programming, Stack. Reported in interviews at Dream11 and 0 others.
Minimum Number of Increments on Subarrays to Form a Target Array is a hard problem that Dream11 has asked, with a 72% acceptance rate. You're given a starting array of zeros and a target array. Each operation lets you pick a subarray and increment all elements by 1. The catch: you need to find the minimum operations to reach the target. It sounds like a greedy or DP problem, and it's tested enough that if it appears in your live assessment, you need a real solution ready. If you haven't drilled the pattern, StealthCoder solves it invisible to the proctor.
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Minimum Number of Increments on Subarrays to Form a Target 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. Built by an Amazon engineer who used it to pass JPMorgan's OA and system design loop.
Get StealthCoderThe key insight is that you can reconstruct the target array greedily by working from left to right and using a stack to track 'heights'. Think of the target as a skyline: whenever you need to increase a value, you're starting new operations; whenever you decrease, you're ending operations. A monotonic stack lets you count how many operations must terminate at each position. The trick most candidates miss: this isn't about the raw values in the target, it's about the *differences* between adjacent elements and how many 'active' increments you need at each step. Greedy fails without the stack structure. If the pattern doesn't click on exam day, StealthCoder surfaces the working solution in seconds, no proctor visibility.
Pattern tags
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Minimum Number of Increments on Subarrays to Form a Target 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. Built by an Amazon engineer who used it to pass JPMorgan's OA and system design loop. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Minimum Number of Increments on Subarrays to Form a Target Array interview FAQ
Is this really a hard problem or is the rating inflated?+
The 72% acceptance rate suggests it's genuinely easier than typical hard problems. However, the algorithm isn't intuitive without the stack pattern. Most candidates who solve it have either seen the monotonic stack trick or worked through greedy intuition carefully. It's a hard-label problem that rewards structured thinking.
What's the actual trick to this problem?+
Model the target as a height profile. Use a monotonic stack to track active increments. The key: every time the target value drops, you end some operations. Count how many end at each position using the stack. This gives you the minimum operations without simulating anything.
How does this relate to the other topics listed?+
Array and Dynamic Programming are broad; this problem uses Greedy logic with a Monotonic Stack implementation. The stack is essential. You could solve it with DP, but the greedy stack approach is optimal and more elegant. Stack knowledge is non-negotiable here.
Will I see this at other companies or just Dream11?+
Dream11 is the only company in the data that's asked this specific problem. It's not a household-name FAANG question. If it shows up in your assessment and isn't from Dream11, it's a variant or inspired problem. The pattern translates to other increment-subarray problems.
How much time should I spend drilling this if it's not my target company?+
If you're interviewing at Dream11, prioritize it. Otherwise, it's a good monotonic stack workout but not essential. The stack and greedy pattern matter more than this specific problem. Spend 30-45 minutes understanding the logic, not memorizing the solution.
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