Bytedance·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Apr 2026

Summary

Bytedance SWE interview, system design flavored but really a deep data structures question. They wanted you to actually know the internals, not just name-drop deque.

Questions Asked (1)

Design a list data structure that supports lpush, lpop, rpush, rpop, and index-based access all in O(1). Walk through the resize strategy and the head/tail pointer arithmetic for a circular buffer backed by a dynamic array.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

I knew deque was the answer immediately but then they said 'describe the pointer arithmetic in detail' and I kind of froze.

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AI HintsAI Generated

Suggested Approach

Start by clarifying that a circular buffer backed by a dynamic array can achieve O(1) for all operations by maintaining head and tail indices and resizing when full. Explain the pointer arithmetic for push/pop at both ends and index-based access using modular arithmetic. Then detail the resize strategy, including when to grow/shrink and how to copy elements in order.

Pro tip: Mention that resizing is amortized O(1) and discuss trade-offs like memory overhead and potential worst-case latency; this shows you understand practical system design beyond just theoretical complexity.

1. Clarify requirements and constraints

Confirm that all operations must be O(1) amortized, and discuss whether index-based access is 0-based or 1-based. Ask about expected usage patterns to inform resize strategy.

2. Describe the circular buffer structure

Explain that you maintain a dynamic array, a head index pointing to the first element, a tail index pointing to the next insertion point at the end, and a size counter. Use modular arithmetic to wrap around.

3. Detail push/pop operations and pointer arithmetic

For lpush: decrement head modulo capacity and insert. For lpop: remove at head and increment head modulo capacity. For rpush: insert at tail and increment tail modulo capacity. For rpop: decrement tail modulo capacity and remove. Update size accordingly.

4. Explain index-based access

To access element at index i, compute (head + i) % capacity. This gives O(1) access as long as the buffer is not resized concurrently.

5. Outline resize strategy

When size equals capacity, double the capacity and copy elements in order from head to tail into the new array, resetting head to 0 and tail to size. When size falls below a quarter of capacity, halve the capacity to save memory. Discuss amortized O(1) and trade-offs.

Key Points to Mention

Use of modular arithmetic to handle wrap-around for head and tail indices.
Maintaining a size counter to distinguish between full and empty states.
Resizing by doubling when full and halving when size is below a threshold (e.g., 1/4 capacity) to avoid thrashing.
Copying elements in correct order during resize to maintain logical sequence.
Amortized O(1) time complexity for push/pop operations due to resizing.
Trade-offs: memory overhead vs. performance, and potential worst-case latency during resize.

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