Apple·Software Engineer·Onsite - System Design / Architecture·Senior

Senior

Jun 2026

Summary

Apple system design round for a software engineering role. The main problem was building a versioned key-value store with snapshot support, and they pushed pretty hard on the efficiency angle once you got the basic structure down.

Questions Asked (1)

Design and implement a key-value map that supports set, get, snapshot, and get-at-snapshot operations, where snapshots must be space-efficient and writes after a snapshot cannot affect earlier snapshot reads.

System DesignAlgorithms & Data StructuresTechnical Trade-offs

Author's notes

The basic structure came to me fast: per-key versioned logs with binary search on snapshot IDs.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a design that balances time and space efficiency, such as a persistent data structure with path copying or a versioned approach. Discuss trade-offs between different implementations and justify your choice based on the operations' expected frequency and snapshot lifetime.

Pro tip: Emphasize that snapshots should be immutable and that writes after a snapshot must not affect earlier snapshots, which is naturally achieved with persistent data structures. Mention that space efficiency can be improved by sharing unchanged nodes between versions.

1. Clarify Requirements

Ask about expected workload (read/write ratio, number of snapshots), memory constraints, and whether snapshots need to be long-lived. This informs the choice of data structure.

2. Propose High-Level Design

Suggest using a persistent balanced binary search tree (e.g., AVL or red-black tree) with path copying for snapshots. Alternatively, consider a versioned hash map with copy-on-write or a log-structured approach.

3. Detail Operations

Explain how set and get work in O(log n) time by traversing and updating the tree. For snapshot, return the root pointer; for get-at-snapshot, traverse the tree from the snapshot's root.

4. Analyze Trade-offs

Compare time and space complexity: path copying uses O(log n) space per write, while full copy uses O(n). Discuss alternatives like versioned arrays or hash maps with version chains.

5. Optimize and Conclude

Mention optimizations like node sharing, structural sharing, and garbage collection of old snapshots. Conclude with why the chosen design meets the requirements.

Key Points to Mention

Persistent data structures (e.g., persistent balanced BST) with path copying for O(log n) time and space per operation.
Immutability of snapshots ensures writes after snapshot do not affect earlier reads.
Space efficiency through structural sharing: unchanged nodes are shared between versions.
Trade-offs: path copying vs. full copy vs. versioned hash map; impact on time and space.
Handling of get-at-snapshot: traverse from the snapshot's root, not the current root.
Potential optimizations: garbage collection of old snapshots, using a versioned array for small key spaces.

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