Amazon·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026

Summary

Amazon SWE coding round with a tricky state-propagation sequence problem. The constraint about the '0' flip rule is what makes it non-trivial, and I spent way too long just staring at the example before the approach clicked.

Questions Asked (1)

You're given a list of values, a binary state string, and an integer m. Build a sequence of length m by repeatedly picking an index where state is '1', appending its value, then flipping any '0' immediately to the right of a '1' across the whole string. Return the lexicographically largest sequence possible.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The flip rule tripped me up for a while.

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AI HintsAI Generated

Suggested Approach

First, clarify the problem constraints and edge cases, then identify the greedy strategy: at each step, pick the available '1' with the largest value to maximize the sequence lexicographically. Simulate the state updates efficiently using a data structure that tracks flips and available indices, and analyze the time and space complexity.

Pro tip: Demonstrate Amazon's Leadership Principles by proactively discussing trade-offs between different data structures (e.g., priority queue vs. segment tree) and their impact on scalability, showing you think about real-world constraints.

1. Clarify the Problem

Ask questions to confirm the rules: how flips propagate, whether multiple flips can occur in one step, and the range of values and m. Ensure you understand the lexicographic comparison for sequences.

2. Identify the Greedy Choice

Recognize that to maximize lexicographically, you should always pick the largest available value from indices where state is '1'. Prove that this greedy choice is optimal by exchange argument.

3. Design an Efficient Simulation

Choose a data structure to efficiently find the maximum value among available '1's and to update the state after flips. Consider a priority queue for available values and a balanced tree or segment tree to track state changes.

4. Analyze Complexity and Trade-offs

Discuss the time and space complexity of your approach. Compare alternatives (e.g., naive simulation vs. optimized) and explain why your choice is suitable for large inputs.

5. Test with Edge Cases

Walk through examples including all '1's, all '0's, m larger than available picks, and cases where flips create new '1's. Verify correctness and performance.

Key Points to Mention

Greedy strategy: always pick the maximum available value to ensure lexicographically largest sequence.
State update mechanism: flipping '0's immediately to the right of '1's, and how this affects future availability.
Data structures: priority queue for max value retrieval, and a segment tree or Fenwick tree for efficient range flips and point queries.
Time complexity: O((n + m) log n) with appropriate data structures, and space complexity O(n).
Edge cases: m greater than number of '1's, all zeros, and values with duplicates.
Trade-offs: simplicity vs. performance, and how to handle large inputs under Amazon's scale.

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