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Optiver·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jul 2026

Summary

Optiver quant engineer interview with a data structures problem that sounds trivial until you're actually sitting there trying to remember how ring buffers work under pressure. The interviewer walked me through it more than I'd like to admit.

Questions Asked (1)

Q1

Design and implement a circular queue class with enQueue, deQueue, Front, Rear, isEmpty, and isFull operations, all running in constant time.

Algorithms & Data StructuresSystem Design
Author's notes

I knew what a circular queue was in the abstract but blanked on the fixed-capacity ring buffer framing until the interviewer nudged me toward it.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements and constraints, then explain the circular queue design using a fixed-size array with two pointers (front and rear) and a size counter. Walk through each operation, emphasizing how the modulo operator enables wrap-around and how the size counter distinguishes full from empty. Finally, discuss edge cases and complexity.

Pro tip: Mention that using a size counter avoids the classic ambiguity of full vs. empty when front equals rear, and that this design is lock-free friendly for concurrent scenarios. Also, briefly note that the same logic applies to a ring buffer in system design.

1. Clarify requirements and constraints

Ask about the expected capacity, data types, thread-safety, and whether dynamic resizing is needed. Confirm that all operations must be O(1) and that the queue is fixed-size.

2. Design the data structure

Propose using a fixed-size array, two integer pointers (front and rear), and a size variable to track the number of elements. Explain that front points to the first element and rear points to the next insertion position.

3. Implement core operations

For enQueue: check isFull, place element at rear, update rear = (rear + 1) % capacity, increment size. For deQueue: check isEmpty, retrieve element at front, update front = (front + 1) % capacity, decrement size. Front and Rear simply return the respective elements if not empty.

4. Handle edge cases and validate

Test scenarios: empty queue, full queue, wrap-around, single element, and multiple enqueue/dequeue cycles. Ensure that front and rear are updated correctly and that size prevents overflow/underflow.

5. Analyze complexity and discuss extensions

State that all operations are O(1) time and O(n) space. Optionally, mention how to make it thread-safe using locks or atomic operations, or how to implement a dynamic circular queue with resizing.

Key Points to Mention

  • Use of modulo operator for circular indexing: (index + 1) % capacity.
  • Maintaining a size counter to easily check isEmpty and isFull, avoiding the need for a reserved slot.
  • Time complexity: all operations are O(1); space complexity: O(capacity).
  • Edge cases: empty queue, full queue, wrap-around, and single element.
  • Thread-safety considerations for concurrent environments (e.g., using locks or atomic variables).
  • Comparison with alternative designs, such as using a linked list or a dynamic array with resizing.

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