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Circle·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say
May 2026Remote

Summary

Circle SWE interview with a meaty system design coding problem centered on an in-memory payment processing component. The question was basically a mini-OOP design session with complexity analysis baked in, which I wasn't fully expecting at this depth.

Questions Asked (1)

Q1

Design and implement an in-memory banking payment component with APIs for scheduling payments, canceling them, removing them under specific conditions, processing due payments, and retrieving top spenders by outgoing total. Define your data structures, explain the time and space complexity of each operation, and walk through edge cases like double-cancellation, removing a successful payment, and ensuring canceled payments don't get executed.

System DesignAlgorithms & Data StructuresData Modeling
Author's notes

This one took a while to fully unpack.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and defining the core entities (Payment, PaymentStatus) and the operations. Then design data structures that support efficient scheduling, cancellation, removal, and top-spender queries, explaining trade-offs. Finally, walk through the implementation, complexity analysis, and edge cases, ensuring correctness and robustness.

Pro tip: Emphasize idempotency and state transitions: ensure operations like cancel and remove are safe to call multiple times and that payments only execute if in the correct state. This shows you think about real-world reliability and data integrity.

1. Clarify requirements and define entities

Ask about expected scale, concurrency, and persistence. Define Payment (id, amount, scheduledTime, status, payer) and PaymentStatus (SCHEDULED, CANCELED, SUCCESSFUL, FAILED).

2. Design data structures

Choose a map for payments by ID, a priority queue (min-heap) for due payments, and a map for user outgoing totals. Consider additional indexes for efficient removal and top-spender queries.

3. Implement core operations

Write methods for schedule, cancel, remove, processDue, and getTopSpenders. Ensure each operation updates all relevant structures atomically and maintains consistency.

4. Analyze time and space complexity

For each operation, state the average and worst-case time complexity and overall space usage. Discuss trade-offs of chosen data structures.

5. Walk through edge cases

Cover double-cancellation, removing a successful payment, canceled payments not executing, processing payments with same timestamp, and handling large numbers of payments.

Key Points to Mention

  • Use a min-heap (priority queue) keyed by scheduled time for efficient due payment processing.
  • Maintain a map from payment ID to Payment object for O(1) lookup and updates.
  • Track user outgoing totals in a hash map, and use a sorted structure (e.g., balanced BST or heap) for top spenders queries.
  • Ensure idempotent operations: canceling an already canceled payment should be a no-op, and removing a successful payment should be disallowed or handled gracefully.
  • When processing due payments, check the payment's status to avoid executing canceled payments.
  • Consider concurrency: use locks or thread-safe data structures if multiple threads may access the component.

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