Start by clarifying requirements and scale, then design the core data model with hotels, room types, and bookings, focusing on efficient availability checks and concurrency control. Use in-memory structures like hash maps and interval trees, and discuss trade-offs between locking granularity and throughput.
Pro tip: Emphasize that concurrency control must be designed from the start, not bolted on; propose a locking strategy that balances correctness and performance, and mention how you would test it under load.
Ask about expected scale (number of hotels, rooms, bookings), concurrency level, and whether bookings can span multiple room types. Confirm that all data is in-memory and persistence is out of scope.
Define classes for Hotel, RoomType, and Booking. Use unique IDs and store hotels in a hash map. For each room type, maintain a data structure to track booked date ranges, such as an interval tree or a sorted list of bookings.
For a given date range and room type, check for overlapping bookings. Use efficient data structures to avoid scanning all bookings, e.g., interval tree or segment tree, and discuss time complexity.
On booking, validate availability and atomically insert the booking. On cancellation, remove the booking and free the dates. Ensure operations are idempotent and handle edge cases like invalid dates.
Use fine-grained locking per room type or optimistic concurrency with versioning. Discuss trade-offs: coarse locks are simple but limit throughput; fine-grained locks improve concurrency but add complexity. Mention deadlock avoidance and testing strategies.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.