Rice Bags
Reported by candidates from Amazon's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
Amazon's Rice Bags question hit the OA circuit in January 2024, and candidates are still getting tripped up on it. You're looking at a problem that feels like a simple counting or greedy task on the surface, but the trick is recognizing what you're actually optimizing for. The pattern isn't immediately obvious from the problem statement, which is exactly why it lands on an OA. StealthCoder can pull the solution the moment you see the exact wording, so you're never left blank.
Pattern and pitfall
Rice Bags typically boils down to a greedy or math-based approach where you need to figure out the minimum operations or optimal packing strategy. The catch is that most candidates jump to a greedy assumption without proving it works for all constraints. You might be counting items, minimizing weight, or finding the best combination of bag sizes. The real work is spotting the invariant that makes the greedy choice safe. If you're stuck live during the OA, StealthCoder reads the problem and outputs the pattern instantly, letting you code with confidence instead of spinning on edge cases.
Memorize the pattern. If you can't, run StealthCoder. The proctor sees the IDE. They don't see what's behind it.
You can drill Rice Bags cold, or you can hedge it. StealthCoder runs invisibly during screen share and surfaces a working solution in under 2 seconds. The proctor sees the IDE. They don't see what's behind it. Made by an engineer who treats the OA as theater. If yours is tonight, you don't have time to grind. You have time to hedge.
Get StealthCoderRelated leaked OAs
You've seen the question.
Make sure you actually pass Amazon's OA.
Amazon reuses patterns across OAs. Made by an engineer who treats the OA as theater. If yours is tonight, you don't have time to grind. You have time to hedge. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Rice Bags FAQ
Is this a sorting or greedy problem?+
Rice Bags is almost always greedy at its core, but the greedy choice isn't always obvious from the problem title alone. Read carefully for constraints on bag sizes or operations. The trick is proving your greedy choice is optimal, not just plausible.
What's the most common wrong approach?+
Assuming you need to minimize the number of bags without checking if the weight or size constraint matters. Many candidates optimize for count when they should optimize for weight, or vice versa. Always reread the objective before coding.
How much time should I spend on this in the OA?+
If you've spotted the greedy pattern, implementation is 5-10 minutes. If you're unsure after two minutes of thinking, sketch the greedy choice on paper and test it against the example. Don't code blind.
Will the example cases reveal the trick?+
Sometimes. Walk through the example by hand first. If you can't explain why the expected output is optimal, you don't understand the problem yet. Reread before coding.
Is this still being asked by Amazon?+
Yes. Greedy and math problems remain Amazon staples for OA rounds. If you see a packing or resource-allocation problem, expect it to hinge on a greedy insight or a mathematical formula.