Minimum Space Wasted From Packaging
A hard-tier problem at 33% community acceptance, tagged with Array, Binary Search, Sorting. Reported in interviews at Two Sigma and 0 others.
You've got an array of package sizes and a series of box dimensions. Pick one box size for each package and minimize wasted space. Two Sigma has asked this. It's a hard problem with a 33% pass rate, which means most candidates either miss the optimization or get stuck on the implementation. The trick isn't obvious from the problem statement. If you blank on the binary search angle during your assessment, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Minimum Space Wasted From Packaging"
Minimum Space Wasted From Packaging 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 a senior engineer who knows the OA is theater. This is the script.
Get StealthCoderThe naive greedy approach fails. You can't just assign each package to the smallest box that fits. The real solution uses sorting and binary search on prefix sums. Sort packages and boxes separately. For each package, binary search to find the smallest box that holds it, then use prefix sums to calculate the total waste across all packages assigned to that box size. The trick is recognizing that you want to partition packages into contiguous groups, where all packages in a group go into the same box size. Most candidates burn time on greedy assignment or miss the prefix sum optimization entirely. If you hit this live and the pattern doesn't click, StealthCoder solves the binary search setup and prefix sum logic instantly.
Pattern tags
You know the problem.
Make sure you actually pass it.
Minimum Space Wasted From Packaging 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 a senior engineer who knows the OA is theater. This is the script. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Minimum Space Wasted From Packaging interview FAQ
Why doesn't greedy assignment work here?+
Greedy assigns each package to the smallest box that fits it, but that fragments waste across multiple box sizes. The optimal solution partitions packages into contiguous groups and assigns each group to a single box size. You need to explore different partitions, which is where binary search enters the picture.
What's the role of prefix sums in this problem?+
Once you've sorted packages and boxes, you use prefix sums to calculate total waste for a contiguous range of packages assigned to a single box size in constant time. Without prefix sums, you'd recalculate the sum for each partition candidate, tanking performance.
Is this still asked at Two Sigma?+
Two Sigma is confirmed in the data. Hard problems with a 33% pass rate are usually reserved for senior roles or follow-up rounds. It's less common than medium-difficulty problems but absolutely in scope if you're targeting them.
How do I know when binary search is the right tool?+
You're searching for a partition boundary where switching to a larger box size reduces total waste. That monotonic property is the signal for binary search. If you see yourself iterating through partitions naively, you've missed the optimization.
What's the actual time complexity?+
Sort packages and boxes separately (O(n log n) and O(m log m)). Binary search on partitions with prefix sum lookups gives O(n log m). Total is O(n log n + m log m + n log m), which is acceptable for the constraints.
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