Openai·Software Engineer·Technical Phone Screen·Senior

Senior

May 2026

Summary

Coding round at OpenAI for a Software Engineer position. The question was a deep dive into serialization design, not just slapping a map together, and they wanted the full picture: error handling, binary format justification, complexity analysis, and tests.

Questions Asked (1)

Build an in-memory key-value store in C++ with put, get, and erase operations, plus serialize and deserialize methods that encode and restore the full store state using only provided byte I/O helpers. Your binary format must handle arbitrary bytes and Unicode, be versioned and length-prefixed, and gracefully reject malformed or truncated input. Also explain your complexity, format trade-offs, and provide unit tests.

System DesignTechnical Trade-offsAlgorithms & Data Structures

Author's notes

This looked like a straightforward map wrapper until the serialization constraints hit.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then design a simple hash map-based store with a clear binary format. Walk through the serialization format, error handling, complexity, and trade-offs, and finish with a testing strategy.

Pro tip: Emphasize robustness: explicitly handle malformed input with clear error codes and avoid undefined behavior. Mention that you'd use length-prefixed fields and a version header to allow future evolution.

1. Clarify requirements and constraints

Ask about expected data sizes, concurrency needs, and whether the byte I/O helpers are blocking or non-blocking. Confirm that the store must handle arbitrary binary keys and values, including null bytes and Unicode.

2. Design the in-memory data structure

Propose using std::unordered_map<std::string, std::string> for average O(1) put/get/erase. Discuss potential alternatives like a custom hash table or std::map for ordered iteration, and justify your choice based on complexity and simplicity.

3. Define the binary serialization format

Specify a versioned, length-prefixed format: a magic number, version, number of entries, then for each entry the key length, key bytes, value length, value bytes. Explain how this handles arbitrary bytes and Unicode (as UTF-8 or raw bytes) and allows forward compatibility.

4. Implement serialization and deserialization with error handling

Describe writing to a byte buffer using the provided I/O helpers, and reading back with validation: check magic, version, lengths, and total bytes consumed. On malformed or truncated input, return an error status and leave the store unchanged.

5. Analyze complexity, trade-offs, and testing

State that put/get/erase are O(1) average, serialize/deserialize are O(n) where n is total bytes. Discuss trade-offs: memory overhead of length prefixes vs. safety, versioning vs. simplicity. Outline unit tests for round-trip, edge cases (empty store, large values, binary data), and malformed inputs.

Key Points to Mention

Use of std::unordered_map for O(1) average operations and discussion of worst-case O(n) due to hash collisions.
Binary format details: magic number, version field, entry count, length-prefixed keys and values to handle arbitrary bytes and Unicode.
Error handling: validate magic, version, lengths, and total bytes; return error codes and avoid partial state changes.
Complexity analysis: O(1) average for put/get/erase, O(n) for serialize/deserialize where n is total bytes.
Trade-offs: memory overhead vs. safety, versioning for forward compatibility, choice of length-prefix size (e.g., 4 bytes vs. varint).
Testing strategy: unit tests for round-trip, empty store, large values, binary data, truncated input, and version mismatch.

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