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

SeniorPass
May 2026

Summary

OpenAI software engineer interview, system design round focused on low-level memory management. The problem had some depth to it and the follow-up discussion pushed into real tradeoff territory.

Questions Asked (1)

Q1

Design a memory allocator that supports coalescing of free blocks to reduce fragmentation.

System DesignAlgorithms & Data StructuresTechnical Trade-offs
Author's notes

Went with a linked list of free blocks and handled merging adjacent blocks on deallocation.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements (e.g., allocation sizes, performance goals, concurrency) and then outline a design using a free list with boundary tags to enable coalescing. Explain the data structures, algorithms for allocation/deallocation, and how coalescing reduces fragmentation, while discussing trade-offs like time vs. space overhead.

Pro tip: Mention real-world allocators like dlmalloc or jemalloc to show practical awareness, and emphasize how your design handles edge cases such as coalescing with adjacent free blocks and avoiding fragmentation.

1. Clarify Requirements and Constraints

Ask about expected allocation patterns, size ranges, performance metrics (throughput, latency), and whether the allocator needs to be thread-safe. This ensures your design targets the right priorities.

2. Choose Core Data Structures

Decide on a free list organization (e.g., segregated free lists by size class) and metadata per block (size, free/used flag, boundary tags). Explain how these enable efficient coalescing.

3. Design Allocation and Deallocation Algorithms

Describe how to find a suitable free block (first-fit, best-fit, etc.), split it if necessary, and update metadata. For deallocation, mark block as free and attempt coalescing with adjacent free blocks using boundary tags.

4. Address Fragmentation and Coalescing

Explain how coalescing reduces external fragmentation by merging adjacent free blocks. Discuss internal fragmentation and strategies to mitigate it (e.g., size classes, splitting).

5. Discuss Trade-offs and Optimizations

Cover trade-offs: time overhead of coalescing vs. memory savings, metadata overhead, and potential concurrency strategies (e.g., per-thread caches, locks). Mention possible optimizations like deferred coalescing.

Key Points to Mention

  • Boundary tags (footer) to enable O(1) coalescing with previous and next blocks.
  • Free list organization: implicit vs. explicit, segregated free lists for faster allocation.
  • Coalescing algorithm: merge with previous and/or next block if free, update free list.
  • Fragmentation types: internal vs. external, and how coalescing addresses external fragmentation.
  • Trade-offs: overhead of metadata, time complexity of coalescing, and impact on allocation speed.
  • Concurrency considerations: thread-local caches, locks, or lock-free approaches for scalability.

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