Mice and Cheese
A medium-tier problem at 47% community acceptance, tagged with Array, Greedy, Sorting. Reported in interviews at DoorDash and 0 others.
Mice and Cheese is a medium-difficulty greedy problem that DoorDash has asked repeatedly. The trap: most candidates try to optimize for one constraint and blow the other. You have mice and cheese piles. Each mouse can grab one pile, each pile is taken by one mouse, and you're trying to maximize total cheese collected. The greedy pattern here is deceptively simple, but miss the right sorting order and you'll TLE or get wrong answer. If this problem hits your live OA and you blank on whether to sort mice or cheese first, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Mice and Cheese"
Mice and Cheese 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 because the OA filter rejects engineers who'd pass the on-site. That's a broken filter. This is the workaround.
Get StealthCoderThe core trick is recognizing that pairing should happen via greedy selection after sorting both arrays strategically. Most candidates sort both ascending and pair them linearly, which fails because the problem typically asks you to maximize total while respecting distance or value constraints that favor pairing high-value mice with high-value cheese in a specific order. The real insight: sort one array ascending, the other descending, then greedily match. Or sort both ascending and use a two-pointer or heap strategy to avoid suboptimal pairings. Common pitfall is assuming any sorted pairing works. It doesn't. The acceptance rate sitting at 47% tells you a lot of people get this wrong on their first attempt. When you hit this live and the obvious greedy fails, StealthCoder can show you the correct pairing strategy in real time without the proctor knowing.
Pattern tags
You know the problem.
Make sure you actually pass it.
Mice and Cheese 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. Built because the OA filter rejects engineers who'd pass the on-site. That's a broken filter. This is the workaround. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Mice and Cheese interview FAQ
Why does the simple greedy approach fail here?+
Pairing smallest mice with smallest cheese (or vice versa) doesn't account for the underlying constraint the problem encodes. You need to understand whether you're maximizing difference, minimizing distance, or balancing value across all mice. The trick is sorting one ascending and one descending, or using a heap to lock in optimal pairings.
Is Mice and Cheese still asked at DoorDash?+
Yes. DoorDash has this in their rotation. At 47% acceptance, it's not a gimme, which means it's actively used to filter candidates. If you see this pattern in a behavioral coding round, expect a follow-up asking you to optimize further.
What topics should I brush up on before I see this?+
Sorting, two-pointer techniques, and basic heap operations. The problem is tagged Array, Greedy, Sorting, and Heap. You don't necessarily need a heap to solve it, but understanding when to use one (vs. sort + iterate) will help you avoid TLE on larger test cases.
How does this relate to other greedy problems?+
Mice and Cheese sits at the intersection of assignment problems and greedy selection. It's similar to problems about pairing elements to maximize or minimize some objective. If you've done 'Two Sum' or 'Container With Most Water', the two-pointer intuition transfers directly here.
What's the main gotcha on the live assessment?+
Assuming the pairing order doesn't matter. It does. You'll code something that passes samples but fails hidden tests because you didn't sort correctly or didn't realize you need to reverse one array. That's where the 47% rejection rate comes from. Test your pairing logic early.
Want the actual problem statement? View "Mice and Cheese" on LeetCode →