Optiver·Software Engineer·Onsite - Coding / Algorithms·Intermediate

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Jul 2026

Summary

Optiver SWE interview had me designing a FIFO queue from scratch and then defending every implementation choice under pressure. Pretty deep dive for what I expected to be a standard data structures round.

Questions Asked (1)

Design a FIFO queue supporting enqueue, dequeue, peek, and isEmpty. Walk through implementations using a singly linked list, a dynamic array, and a circular buffer, then compare their trade-offs in terms of time complexity, space overhead, cache behavior, and amortized resizing costs. Also cover edge cases like underflow and overflow, and how you'd handle concurrent access.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

This started normal enough and then kept going.

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AI HintsAI Generated

Suggested Approach

Start by defining the FIFO queue interface and its operations, then systematically walk through each implementation (singly linked list, dynamic array, circular buffer), analyzing time and space complexity, cache behavior, and resizing costs. Compare trade-offs explicitly, address edge cases like underflow/overflow, and discuss concurrency strategies such as locks or lock-free approaches.

Pro tip: Emphasize that the optimal implementation depends on the use case: for example, a circular buffer is ideal for fixed-size, high-throughput scenarios due to cache efficiency, while a linked list offers flexibility at the cost of memory overhead. Also, mention that in concurrent settings, lock-free queues using atomic operations can outperform lock-based ones under high contention.

1. Define the Queue ADT and Operations

Clearly state the FIFO queue interface: enqueue (add to rear), dequeue (remove from front), peek (view front), and isEmpty. Specify expected behavior for edge cases like empty queue.

2. Analyze Singly Linked List Implementation

Describe using head and tail pointers for O(1) enqueue and dequeue. Discuss space overhead (pointers per node), cache behavior (poor locality), and no resizing costs.

3. Analyze Dynamic Array Implementation

Explain using a resizable array with front and rear indices, handling wrap-around or shifting elements. Cover amortized O(1) enqueue/dequeue with occasional O(n) resizing, better cache locality, but potential wasted space.

4. Analyze Circular Buffer Implementation

Describe fixed-size array with head and tail pointers that wrap around. Achieve O(1) operations, excellent cache locality, but need to handle overflow (full buffer) and underflow (empty buffer).

5. Compare Trade-offs and Discuss Concurrency

Summarize trade-offs in time complexity, space overhead, cache behavior, and resizing costs. Then discuss concurrency: lock-based (mutex) vs lock-free (atomic operations) approaches, highlighting pros and cons.

Key Points to Mention

Time complexity: All implementations achieve O(1) for enqueue, dequeue, peek, and isEmpty, but dynamic array may have amortized O(1) due to resizing.
Space overhead: Linked list has per-node pointer overhead; dynamic array may have unused capacity; circular buffer has fixed capacity with no overhead if sized correctly.
Cache behavior: Circular buffer and dynamic array have better cache locality due to contiguous memory; linked list suffers from poor locality.
Amortized resizing: Dynamic array resizing doubles capacity, leading to amortized O(1) enqueue, but occasional O(n) cost; circular buffer avoids resizing but may overflow.
Edge cases: Underflow (dequeue/peek on empty queue) should throw exception or return sentinel; overflow (enqueue on full circular buffer) should throw or block.
Concurrency: Use mutex for simplicity, but lock-free queues (e.g., Michael-Scott queue) offer better scalability under contention; discuss ABA problem and memory reclamation.

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