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Openai·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say
May 2026Remote

Summary

75-minute systems coding screen for an infra/inference team at OpenAI. The whole thing was basically one deep problem: design a memory allocator from scratch, then keep optimizing it until the interviewer was satisfied with the complexity.

Questions Asked (6)

Q1

Design a memory allocator with malloc and free operations. malloc should return the start address of the leftmost available block of sufficient size, and free should release memory and automatically merge with adjacent free blocks. The interviewer will reject O(n) solutions and push you toward O(log m).

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

Started with the linked list approach because it felt natural and I wanted to get something working.

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AI HintsAI Generated

Suggested Approach

Use a balanced binary search tree (e.g., red-black tree) keyed by block size to find the smallest sufficient free block in O(log m). Maintain a doubly linked list of all blocks in address order to enable O(1) merging with adjacent free blocks during free. For malloc, if the chosen block is larger than requested, split it and reinsert the remainder into the tree.

Pro tip: Mention that you would use an intrusive data structure (embedding tree/list pointers in free blocks) to avoid extra memory overhead, and discuss how to handle edge cases like merging at the start/end of the heap.

1. Clarify requirements and constraints

Ask about alignment, thread safety, and whether the allocator needs to handle arbitrary sizes or fixed-size pools. Confirm that O(log m) is required for both malloc and free.

2. Design data structures

Propose a balanced BST (e.g., red-black tree) keyed by block size for free blocks, and a doubly linked list of all blocks in address order. Explain how each block stores pointers for both structures.

3. Implement malloc

Search the BST for the smallest free block with size >= requested. If found, remove it from the BST, split if larger, and return the address. If not found, return NULL (or request more memory from OS).

4. Implement free

Insert the freed block into the address-ordered list, then check and merge with adjacent free blocks. Remove merged blocks from the BST and insert the combined block.

5. Analyze complexity and trade-offs

Explain that both operations are O(log m) due to BST operations. Discuss overhead of pointers, potential fragmentation, and alternatives like segregated free lists.

Key Points to Mention

  • Use of a balanced BST (e.g., red-black tree) keyed by block size to achieve O(log m) search for the smallest sufficient block.
  • Maintain a doubly linked list of all blocks in address order to enable O(1) access to adjacent blocks for merging.
  • Splitting larger blocks during malloc to minimize internal fragmentation, and reinserting the remainder into the BST.
  • Merging adjacent free blocks during free by checking neighbors in the address-ordered list and updating the BST accordingly.
  • Handling edge cases: merging at the beginning/end of the heap, and ensuring the BST remains balanced after removals/insertions.
  • Trade-offs: memory overhead for pointers, potential for external fragmentation, and alternatives like segregated free lists or buddy allocators.

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

Q2

How would you handle the four merge cases when freeing a block, specifically when adjacent blocks may or may not already be free?

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

This is where I fumbled.

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AI HintsAI Generated

Suggested Approach

Start by clarifying that you're discussing a boundary-tag or explicit free list allocator, then systematically walk through the four cases based on the status of the previous and next blocks. For each case, describe the merge operation and how it updates the free list and block headers, emphasizing the importance of coalescing to reduce fragmentation.

Pro tip: Mention that you can simplify the logic by using boundary tags and a doubly-linked free list, and that handling the four cases explicitly avoids subtle bugs like double-free or lost blocks. Also, note that in practice, you might combine cases by always merging with previous if free, then checking next.

1. Identify the four cases

Clearly state the four possible scenarios based on whether the previous and next blocks are free or allocated: (1) both allocated, (2) previous free, next allocated, (3) previous allocated, next free, (4) both free.

2. Describe case 1: neither adjacent block is free

Simply mark the current block as free and add it to the free list. No coalescing occurs.

3. Describe case 2: previous block is free

Merge the current block with the previous free block by updating the previous block's size to include the current block, and remove the current block from consideration (it's absorbed). Update the free list if necessary.

4. Describe case 3: next block is free

Merge the current block with the next free block by updating the current block's size to include the next block, and remove the next block from the free list. Mark the current block as free.

5. Describe case 4: both adjacent blocks are free

Merge all three blocks into one large free block. Update the previous block's size to include both the current and next blocks, and remove both the current and next blocks from the free list. The previous block remains in the free list.

Key Points to Mention

  • Boundary tags (storing size and allocation status at both ends of a block) to enable constant-time access to adjacent blocks' status.
  • Doubly-linked free list to efficiently remove blocks during coalescing.
  • The importance of coalescing to combat external fragmentation.
  • Edge cases: block at the beginning or end of the heap (no previous or next block).
  • Time complexity: O(1) for each case with proper data structures.
  • Potential optimizations: deferred coalescing or segregated free lists.

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

Q3

How would you extend the allocator to ensure all returned addresses are aligned to a specific boundary, like multiples of 8?

System DesignTechnical Trade-offs
Author's notes

They asked this as a follow-up after the core implementation.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the allocator's current behavior and the alignment requirement, then propose a general solution: round up the requested size to a multiple of the alignment and ensure the returned pointer is aligned. Discuss trade-offs like internal fragmentation, performance overhead, and compatibility with existing free/realloc operations.

Pro tip: Mention that alignment must be handled in both allocation and deallocation, and that using a header to store the original allocation size can simplify freeing. Also, consider using standard functions like aligned_alloc or posix_memalign when available, but be prepared to implement manually for portability.

1. Clarify requirements and constraints

Ask about the alignment boundary (e.g., 8 bytes), whether it's power-of-two, and if the allocator must support arbitrary alignments. Confirm if the allocator is used in a specific context (e.g., embedded, kernel) that affects available primitives.

2. Explain the core alignment technique

Describe rounding up the requested size to a multiple of the alignment and ensuring the returned address is aligned. For manual implementation, allocate extra space and adjust the pointer, storing metadata to recover the original block.

3. Address deallocation and metadata

Explain how free() will locate the original allocation: e.g., store the original pointer or size in a header just before the aligned address. Ensure realloc and other operations respect alignment.

4. Discuss trade-offs and alternatives

Cover internal fragmentation (wasted bytes per allocation), performance impact of extra arithmetic, and potential use of platform-specific functions (aligned_alloc, posix_memalign) versus manual implementation.

5. Consider edge cases and testing

Mention handling alignment of 0 or 1, very large alignments, and ensuring thread safety if applicable. Suggest testing with various sizes and alignments to verify correctness.

Key Points to Mention

  • Rounding up allocation size to a multiple of alignment to maintain alignment for subsequent allocations.
  • Storing metadata (e.g., original pointer or size) to enable correct deallocation.
  • Internal fragmentation and its impact on memory efficiency.
  • Using standard aligned allocation functions (aligned_alloc, posix_memalign) when available.
  • Ensuring alignment is preserved through realloc and other allocator operations.
  • Performance considerations: extra arithmetic and potential cache effects.

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

Q4

How would you implement realloc, resizing an allocated block in-place while preserving its contents?

System DesignAlgorithms & Data Structures
Author's notes

Knew the concept: check if the right neighbor is free and has enough space, extend in-place if so, otherwise allocate a new block and copy.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the constraints: realloc must resize a block in-place while preserving contents, which is only possible if the allocator can extend or shrink the block without moving it. Then explain the algorithm: check if the new size fits within the current block or can be extended into adjacent free space; if not, fall back to allocating a new block, copying data, and freeing the old one. Finally, discuss trade-offs and edge cases like alignment, fragmentation, and failure handling.

Pro tip: Emphasize that true in-place resizing depends on the allocator's ability to coalesce with adjacent free blocks, and mention that many real-world realloc implementations fall back to copy-and-free when in-place isn't possible. This shows you understand both the ideal and practical constraints.

1. Clarify requirements and constraints

Confirm that the goal is to resize an allocated block in-place while preserving contents, and discuss what 'in-place' means when the block cannot be extended (e.g., fallback to copy).

2. Check if in-place resizing is possible

Determine if the new size fits within the current block or can be achieved by merging with adjacent free blocks; if shrinking, simply update metadata.

3. Implement the in-place resize logic

If extending, attempt to coalesce with the next free block; if successful, update the block size and return the same pointer. If shrinking, split the block if the remainder is large enough.

4. Handle fallback: allocate, copy, free

If in-place resizing fails, allocate a new block of the requested size, copy the old contents (up to the minimum of old and new sizes), free the old block, and return the new pointer.

5. Address edge cases and error handling

Discuss alignment, zero-size requests, failure to allocate (return NULL and leave original block intact), and performance implications.

Key Points to Mention

  • Memory allocator internals: block headers, free lists, coalescing adjacent free blocks
  • In-place extension requires contiguous free space after the block; otherwise fallback to copy
  • Shrinking can be done in-place by splitting the block and returning the excess to the free list
  • Preserving contents: copy min(old_size, new_size) bytes when moving
  • Alignment requirements and how they affect block sizes and splitting
  • Failure handling: return NULL, keep original block unchanged, and avoid memory leaks

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

Q5

What locking strategy would you use to make the allocator thread-safe under concurrent access?

System DesignTechnical Trade-offs
Author's notes

Talked through a coarse global lock as the baseline, then mentioned per-size-class locks as a middle ground, then lock-free approaches as the ceiling.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the allocator's requirements (e.g., throughput, latency, scalability) and then discuss locking strategies ranging from coarse-grained to fine-grained, highlighting trade-offs. Emphasize a hybrid approach like per-thread caches with periodic global synchronization, and justify your choice based on the context.

Pro tip: Mention that the best locking strategy depends on the allocator's design and workload; for example, a thread-local cache can eliminate most lock contention, but you must handle cross-thread deallocation carefully. This shows you understand real-world allocator implementations like tcmalloc or jemalloc.

1. Clarify Requirements and Constraints

Ask about the expected concurrency level, performance goals (throughput vs. latency), and whether the allocator is general-purpose or specialized. This ensures your answer is tailored to the scenario.

2. Discuss Locking Granularity Options

Compare coarse-grained (single global lock) vs. fine-grained (per-size-class, per-arena) locks. Explain how finer granularity reduces contention but increases complexity and overhead.

3. Propose a Hybrid or Lock-Free Approach

Suggest thread-local caches to avoid locks on the fast path, with periodic global synchronization for memory reclamation. Alternatively, mention lock-free data structures (e.g., using atomics) for specific operations.

4. Address Trade-offs and Edge Cases

Discuss issues like false sharing, lock contention under high load, and cross-thread deallocation. Explain how your strategy handles these, possibly with techniques like sharded locks or epoch-based reclamation.

5. Conclude with a Recommendation

Summarize your chosen strategy, justifying it based on the requirements. Acknowledge that no single solution is perfect and that the choice depends on the specific use case.

Key Points to Mention

  • Coarse-grained vs. fine-grained locking and their impact on contention and scalability
  • Thread-local caches (e.g., tcmalloc's per-thread cache) to minimize lock usage
  • Lock-free or wait-free techniques using atomic operations for metadata updates
  • Sharded or per-arena locks to reduce contention across multiple threads
  • Trade-offs between simplicity, performance, and memory overhead
  • Handling cross-thread deallocation and memory reclamation safely

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

Q6

How would you detect and guard against double-free or use-after-free bugs in your allocator?

System DesignTechnical Trade-offs
Author's notes

Said you could maintain a separate set of currently allocated (address, size) pairs and validate on every free call.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the allocator's design and constraints, then discuss detection techniques (e.g., canaries, quarantine, metadata checks) and guard mechanisms (e.g., memory tagging, reference counting). Emphasize trade-offs between performance overhead and safety, and how you would integrate these into the allocator's lifecycle.

Pro tip: Mention that you would use a combination of compile-time instrumentation (like ASan) during development and lightweight runtime checks in production, and that you'd consider the allocator's specific use case (e.g., long-running services vs. short-lived processes) to balance safety and performance.

1. Clarify requirements and constraints

Ask about the allocator's purpose, performance requirements, and deployment environment to tailor the detection and guard strategies.

2. Detection techniques

Describe methods to detect double-free and use-after-free, such as canaries, quarantine zones, metadata validation, and memory tagging.

3. Guard mechanisms

Explain preventive measures like reference counting, ownership models, and hardware-assisted features (e.g., ARM MTE) to guard against these bugs.

4. Trade-offs and integration

Discuss performance overhead, complexity, and how to integrate these mechanisms into the allocator without disrupting existing functionality.

5. Testing and validation

Outline how you would test the allocator using fuzzing, sanitizers, and stress tests to ensure the guards are effective.

Key Points to Mention

  • Canaries and magic numbers to detect corruption
  • Quarantine zones to delay reuse of freed memory
  • Metadata validation (e.g., checking if pointer is in free list)
  • Reference counting or ownership models to prevent premature frees
  • Hardware-assisted memory tagging (e.g., ARM MTE, SPARC ADI)
  • Performance overhead and trade-offs (e.g., memory footprint, latency)

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