This is the kind of problem where the basic get/set feels easy and then you realize the rollback part is where all the complexity lives.
Start by clarifying requirements: what operations are needed (get, put, delete), how rollback is triggered (e.g., by timestamp or transaction ID), and expected scale. Then propose a design using versioning or snapshots, and discuss trade-offs between memory, latency, and complexity. Finally, outline an implementation with data structures and algorithms, and mention how you would test it.
Pro tip: Emphasize the importance of defining rollback semantics early—whether it's rollback to a specific version, undoing a transaction, or reverting to a snapshot—as this drastically affects the design and prevents over-engineering.
Ask questions to understand the scope: what operations are supported, how rollback is specified (e.g., by version, timestamp, or transaction), concurrency needs, and persistence requirements.
Outline a design that supports rollback, such as maintaining a version history per key, using a log of operations, or taking periodic snapshots. Discuss how reads and writes work in this design.
Describe the specific data structures (e.g., hash map with versioned values, linked list of versions, or copy-on-write) and algorithms for put, get, delete, and rollback. Analyze time and space complexity.
Compare approaches: versioning vs. snapshots vs. operation logs. Discuss trade-offs in memory usage, latency, and complexity. Mention optimizations like garbage collection of old versions or using persistent data structures.
Sketch how you would implement the core operations in code (e.g., in Python or Java), and describe test cases including edge cases like rolling back to a non-existent version or concurrent modifications.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.