Amazon·Software Engineer·Online Assessment (OA)·Intermediate

Intermediate

Jun 2026

Summary

Amazon SWE online assessment with a simulation-style coding problem involving priority queues and some arithmetic logic. Nothing behavioral, just straight into the problem.

Questions Asked (1)

You have n VM types each with a limited stock count. Customers arrive one by one and always rent from the VM type with the highest current availability. Each rental costs the sum of the current lowest non-zero availability and the highest availability across all VM types. After each rental, that VM type's count drops by 1. Find the total revenue after serving all m customers.

Algorithms & Data Structures

Author's notes

The revenue formula tripped me up at first.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and edge cases, then propose an efficient algorithm using a max-heap for the highest availability and a min-heap for the lowest non-zero availability, updating both after each rental. Analyze the time and space complexity, and discuss potential optimizations or alternative approaches.

Pro tip: Demonstrate awareness of real-world constraints by discussing how to handle large n and m, and mention that the min-heap must ignore zero counts to correctly compute the lowest non-zero availability.

1. Understand the problem

Restate the problem in your own words, confirm the rules (e.g., customers always choose the VM type with the highest current availability, cost formula), and ask clarifying questions about constraints and edge cases.

2. Identify data structures

Recognize that you need to efficiently find the maximum availability and the minimum non-zero availability. A max-heap and a min-heap (or a balanced BST) are suitable.

3. Design the algorithm

Outline the steps: initialize heaps with VM counts, for each customer, extract max, compute cost using min non-zero, decrement max, update heaps, and accumulate revenue.

4. Analyze complexity

State the time complexity (O((n + m) log n)) and space complexity (O(n)), and discuss potential improvements or trade-offs.

5. Test with examples

Walk through a small example to verify correctness, including edge cases like zero counts or all counts becoming zero before m customers are served.

Key Points to Mention

Use a max-heap to track the VM type with the highest availability.
Use a min-heap to track the lowest non-zero availability, ensuring zero counts are excluded.
Update both heaps after each rental to reflect the decremented count.
Handle the case where all VM types have zero availability before serving all customers.
Time complexity: O((n + m) log n) due to heap operations.
Space complexity: O(n) for storing the heaps.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.