Openai·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say

May 2026

Summary

System design interview at OpenAI for a software engineer role, centered entirely on implementing a memory allocator from scratch. The question was dense and covered a lot of ground, from data structure justification to fragmentation handling to complexity analysis. Felt like a mini systems course crammed into one session.

Questions Asked (1)

Design and implement a simulated memory allocator with allocate(size) and free(ptr) operations over a fixed-size contiguous byte array. Cover data structure selection, alignment, fragmentation handling, coalescing of adjacent free blocks, and time/space complexity. Also discuss first-fit vs best-fit vs next-fit trade-offs and how you'd test and benchmark it.

System DesignAlgorithms & Data StructuresTechnical Trade-offs

Author's notes

This was a lot.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then outline a design using a free list with block headers, explaining allocation policies, coalescing, and alignment. Walk through the implementation details, analyze complexity, compare fit strategies, and finish with a testing and benchmarking plan.

Pro tip: Emphasize the importance of alignment and coalescing for real-world performance, and mention how you would instrument the allocator to measure fragmentation and throughput under various workloads.

1. Clarify Requirements and Constraints

Ask about expected allocation sizes, alignment requirements, thread safety, and performance goals to tailor the design.

2. Design Data Structures

Propose a free list (implicit or explicit) with block headers storing size and free/used status, and explain how to handle alignment and splitting.

3. Implement Allocation and Free

Detail the allocate and free algorithms, including searching the free list, splitting blocks, updating headers, and coalescing adjacent free blocks.

4. Analyze Complexity and Trade-offs

Discuss time and space complexity of operations, and compare first-fit, best-fit, and next-fit policies in terms of speed, fragmentation, and memory utilization.

5. Testing and Benchmarking Strategy

Outline unit tests for correctness, stress tests for fragmentation, and benchmarks measuring allocation/free latency and memory overhead under different workloads.

Key Points to Mention

Use of block headers to store size and status, enabling coalescing and alignment.
Alignment considerations: ensure returned pointers are aligned to at least 8 or 16 bytes.
Coalescing adjacent free blocks to reduce external fragmentation.
Time complexity: O(n) for first/best/next-fit in worst case, but can be optimized with segregated free lists.
Space overhead: headers add per-block overhead; trade-off between overhead and fragmentation.
Testing: unit tests for edge cases (zero-size, double-free), stress tests with random patterns, and benchmarks comparing policies.

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