Distribute Money to Maximum Children
A easy-tier problem at 19% community acceptance, tagged with Math, Greedy. Reported in interviews at Zendesk and 1 others.
Distribute Money to Maximum Children lands on assessments at Apple and Zendesk, yet almost 81% of candidates fail it. That's not because the algorithm is hard. It's because most people overthink it and miss the greedy insight on their first read. You see a distribution problem and think dynamic programming or simulation. The trick is simpler. If you blank on it during the live OA, StealthCoder runs invisibly during screen share and surfaces the pattern in seconds, so you move on to harder problems instead of burning 15 minutes on an easy.
Companies that ask "Distribute Money to Maximum Children"
Distribute Money to Maximum Children 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 StealthCoderThis problem boils down to Math and Greedy. You want to distribute money to as many children as possible, which means you should give each child the minimum valid amount. The greedy move: start with the smallest valid distribution per child, then see how many children you can actually afford. Most candidates try to simulate the distribution or build a recursive solution when the answer is just division with a boundary check. The failure isn't algorithmic complexity, it's pattern recognition under time pressure. Once you see it's about maximizing count by minimizing per-child spend, the code writes itself. StealthCoder handles the moment you second-guess yourself and reach for the wrong approach.
Pattern tags
You know the problem.
Make sure you actually pass it.
Distribute Money to Maximum Children recycles across companies for a reason. It's easy-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.
Distribute Money to Maximum Children interview FAQ
Why does this problem have such a low acceptance rate if it's marked easy?+
The low pass rate reflects reading speed and pattern recognition under pressure, not difficulty. Candidates misread the goal, overthink the constraint, or jump to a complex solution when greedy works. It's easy once you see the trick, but the trick isn't obvious in 90 seconds of cold reading.
Is this still asked at Apple and Zendesk?+
Yes. Both companies have reported this problem in recent cycles. It appears in early-round assessments where the goal is to filter for clarity of thought, not coding prowess. It's a screening question, not a final-round one.
What's the actual trick to this problem?+
Greedy: maximize the child count by giving each child the smallest valid amount. Don't simulate or track individual children. Use math to determine the answer directly. The pattern is about minimizing per-child cost, not optimizing a complex state.
How does Math relate to Greedy here?+
Math is the tool, Greedy is the strategy. You use arithmetic to compute how many children you can afford, then verify the boundary condition. No loops, no DP. Just division and a conditional check.
Should I prepare this problem if I'm interviewing at Apple or Zendesk?+
Yes. Both companies include it in their reported cycles. It's a low-stakes filter that knocks out candidates who panic or over-engineer. Knowing the pattern prevents a wasted 15 minutes and shows clarity under pressure.
Want the actual problem statement? View "Distribute Money to Maximum Children" on LeetCode →