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

Intermediate
Jun 2026

Summary

Coinbase software engineer interview centered on a multi-level in-memory file system design problem. The progression from basic CRUD up through prefix aggregation and then into more advanced features like quotas or copy/move made it feel less like a single question and more like a whole coding session packed into one problem.

Questions Asked (1)

Q1

Design and implement an in-memory file storage system, starting with basic file operations (create, read, update, delete) and then extending it through multiple levels: directory listing, file size aggregation by prefix, and advanced features like user quotas or copy/move operations.

System DesignAlgorithms & Data StructuresTechnical Trade-offs
Author's notes

The first two levels felt manageable.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and defining the core data model, then implement basic CRUD operations with a simple in-memory structure. Progressively extend the design to support directory listing, prefix-based size aggregation, and advanced features like quotas and copy/move, discussing trade-offs at each step.

Pro tip: Demonstrate foresight by designing for extensibility from the start—e.g., using a tree structure that naturally supports directories and prefixes—and explicitly discuss how your choices impact performance and scalability as features are added.

1. Clarify Requirements and Scope

Ask questions to understand expected operations, data volume, concurrency needs, and performance constraints. Confirm whether the system is single-threaded or needs thread-safety.

2. Design Core Data Model and Basic Operations

Propose a data structure (e.g., a tree or a map with path keys) that supports create, read, update, and delete efficiently. Explain how you would implement each operation.

3. Extend to Directory Listing and Prefix Aggregation

Describe how to list directory contents and compute total size for a given prefix. Discuss whether to maintain aggregated metadata (e.g., subtree sizes) for efficiency.

4. Add Advanced Features: Quotas and Copy/Move

Explain how to enforce user quotas (e.g., track per-user usage) and implement copy/move operations, considering atomicity and consistency.

5. Analyze Trade-offs and Optimizations

Discuss time/space complexity of operations, potential bottlenecks, and possible optimizations like caching, lazy aggregation, or concurrency control.

Key Points to Mention

  • Choice of data structure (e.g., trie, tree, hash map) and its impact on operation complexity
  • Handling of path normalization and edge cases (e.g., root directory, nested paths)
  • Efficiency of prefix-based size aggregation: on-the-fly vs. precomputed subtree sizes
  • Concurrency considerations: thread-safety, locking granularity, and atomicity of operations
  • Quota enforcement: per-user tracking, checking before writes, and handling quota exceeded scenarios
  • Copy/move semantics: deep vs. shallow copy, handling cycles, and atomicity

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