Amazon·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Jul 2026Remote

Summary

Amazon SWE coding round, one problem the whole time. Seemed straightforward at first but the commit semantics tripped me up more than I expected.

Questions Asked (1)

Design and implement a Layer class that supports put(key, value), get(key), commit_batch(), and get_state() operations, where commit_batch collapses all current state into a permanent snapshot and discards prior intermediate states. Optimize for both performance and memory given up to 10,000 operations.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

The put and get parts were fine, like five minutes tops.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements and constraints, especially the semantics of commit_batch and get_state. Then propose a design using a hash map for the current layer and a persistent snapshot for committed state, discussing trade-offs between copy-on-write and versioning. Finally, analyze time and space complexity for up to 10,000 operations and suggest optimizations like lazy copying or immutable snapshots.

Pro tip: Emphasize that commit_batch should be O(1) or amortized O(1) by using copy-on-write or persistent data structures, and that get_state should return an immutable snapshot to avoid unintended mutations. This shows you understand both performance and correctness in a production setting.

1. Clarify Requirements and Constraints

Ask about the expected frequency of each operation, whether keys are strings or integers, and the exact semantics of commit_batch and get_state (e.g., does get_state return a copy or a reference?).

2. Propose a Data Structure Design

Suggest using a hash map for the current layer and a separate structure for committed snapshots. Discuss options like copy-on-write, versioned maps, or persistent data structures (e.g., immutable maps).

3. Define Operations and Complexity

Specify how put, get, commit_batch, and get_state work, and analyze their time and space complexity. Highlight that commit_batch should be efficient, ideally O(1) or O(number of changes).

4. Discuss Trade-offs and Optimizations

Compare approaches: copying the entire map on commit vs. lazy copying vs. using a persistent data structure. Discuss memory overhead, read/write performance, and concurrency considerations.

5. Handle Edge Cases and Testing

Mention edge cases like empty commits, overwriting keys, and concurrent access. Suggest unit tests for correctness and performance benchmarks for up to 10,000 operations.

Key Points to Mention

Use a hash map for O(1) average put/get operations.
commit_batch should collapse state efficiently, e.g., by swapping references or using copy-on-write.
get_state should return an immutable snapshot to prevent external modification.
Consider memory overhead: avoid deep copying large maps on every commit.
Discuss versioning or persistent data structures (e.g., HAMT) for efficient snapshots.
Analyze worst-case scenarios and ensure scalability to 10,000 operations.

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