Removing Minimum Number of Magic Beans
A medium-tier problem at 44% community acceptance, tagged with Array, Greedy, Sorting. Reported in interviews at DE Shaw and 0 others.
DE Shaw asked this one. You've got an array of magic beans, and you need to remove the minimum number to satisfy some constraint. Acceptance hovers around 43%, which means most candidates either miss the greedy pattern or code it wrong on first pass. The trick isn't obvious from the problem statement alone. If this lands in your live assessment and you're not immediately certain of the approach, StealthCoder surfaces a working solution in seconds, invisible to the proctor. You don't have time to thrash on the logic.
Companies that ask "Removing Minimum Number of Magic Beans"
Removing Minimum Number of Magic Beans 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 Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE.
Get StealthCoderThe core insight is that you want to maximize beans kept, which means minimizing those removed. The constraint typically involves relationships between adjacent elements or a cumulative property. Sorting almost always comes first, then you enumerate candidate removal scenarios. A greedy choice works when you can prove that keeping certain beans doesn't block a better solution downstream. Prefix sums let you validate cumulative conditions fast. Most candidates try a brute-force two-pointer pass or mess up the enumeration order. StealthCoder is your hedge here: if the greedy pattern doesn't click during the OA and you're stalled, you get the right structure immediately and can code it cleanly under time pressure.
Pattern tags
You know the problem.
Make sure you actually pass it.
Removing Minimum Number of Magic Beans recycles across companies for a reason. It's medium-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 Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Removing Minimum Number of Magic Beans interview FAQ
Why is sorting the first step?+
Sorting lets you reason about the problem monotonically. Once you sort, greedy choices become provable: keeping the smallest beans usually minimizes removals. It also makes prefix sum checks cheap. Without sorting, you're gambling on order.
What's the typical pitfall?+
Candidates enumerate removal sets but forget to validate the constraint after each removal. Or they enumerate wrong: trying random subsets instead of testing each position methodically. Enumeration must be exhaustive and systematic.
How does prefix sum fit?+
After sorting and removing candidates, you need to verify cumulative properties fast. Prefix sums let you check any range sum in O(1). Without it, you re-compute sums per candidate and TLE.
Is this still asked at DE Shaw?+
Yes. DE Shaw is the only company in the reports for this problem. That signal alone makes it worth drilling if you're interviewing there. Medium difficulty, 43% acceptance, means it filters hard.
Do I need to code all five topics?+
You'll use sorting, greedy logic, and prefix sum for sure. Enumeration is your loop structure: iterate candidates, check each. Array is just the data structure. Master sorting and greedy first, then optimize with prefix sums.
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