I started with state shape and that was probably the right call.
Start by clarifying requirements and constraints, then outline the component's state and data models before diving into validation and error handling. Structure your answer around the user flow: date selection, guest count, pricing, validation, and submission. Emphasize trade-offs and edge cases to demonstrate depth.
Pro tip: Treat the widget as a state machine with distinct states (e.g., loading, valid, invalid, sold-out) and discuss how you'd handle asynchronous price updates and race conditions. This shows you think about real-world complexity beyond the happy path.
Ask questions to understand scope: Are prices fetched from an API? What are the room capacity rules? How should sold-out dates be determined? This ensures you address the right problems.
Outline the state variables (dates, guest counts, price, validation errors, loading states) and the data models for room, reservation, and pricing. Consider using a single state object or multiple useState hooks.
Describe validation rules for dates (check-out after check-in), guest count (adults + children <= capacity), and sold-out status. Explain how errors are surfaced to the user and how they affect the Book Now button.
Explain how pricing is calculated based on dates and guest counts, and how you'd fetch updated prices (e.g., debouncing, loading indicators, handling stale responses).
Describe the submit flow: disabling the button when invalid, showing a confirmation dialog, and handling the reservation API call with success/error states.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Structure your answer by first clarifying the widget's requirements and constraints, then systematically address each edge case category (minimum nights, partial availability, timezone/DST, price rounding) with specific testing strategies. Emphasize a combination of unit tests, integration tests, and property-based testing to cover boundary conditions and real-world scenarios.
Pro tip: Demonstrate maturity by discussing how you would prioritize edge cases based on business impact and likelihood, and mention the importance of logging and monitoring in production to catch unforeseen edge cases.
Ask questions to understand the widget's exact behavior, such as how minimum night requirements interact with partial availability and how timezones are handled. Confirm assumptions about price rounding rules and DST handling.
For minimum nights, consider boundaries like exactly meeting the requirement, one night short, and zero nights. For partial availability, test windows that start/end mid-day, overlap with minimum stays, and have gaps. For timezones/DST, test transitions like spring forward and fall back, and cross-timezone bookings. For price rounding, test rounding at .5, currency-specific rules, and cumulative rounding errors.
Use unit tests for isolated logic (e.g., price rounding), integration tests for interactions (e.g., availability with timezones), and property-based tests to generate random valid/invalid inputs. Consider mocking time for DST tests and using fixed dates.
Prioritize edge cases based on business impact (e.g., DST causing off-by-one errors) and automate regression tests. Include monitoring in production to detect edge case failures.
Run tests, analyze failures, and refine both the widget and tests. Consider edge cases that might emerge from user behavior and update tests accordingly.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.