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Among Low-Level Design problems, the Hotel Booking System stands as one of the most instructive and challenging case studies. It combines the complexity of temporal data management with intricate business rules, multi-stakeholder workflows, and real-world constraints that push the boundaries of object-oriented design.
Unlike simpler systems where state is relatively static, a hotel booking system deals with time-sensitive inventory—rooms that exist in a perpetual state of availability, pending, reserved, occupied, and back again. This temporal dimension introduces complexities that many engineers underestimate until they're deep in implementation.
By the end of this page, you will understand how to systematically analyze requirements for a hotel booking system—identifying functional needs, non-functional constraints, stakeholder perspectives, and the subtle complexities that separate amateur designs from production-ready architectures. This foundational analysis will inform every design decision in subsequent pages.
Before diving into requirements, we must deeply understand the problem domain. A hotel booking system operates at the intersection of hospitality management, inventory control, and e-commerce—each bringing distinct challenges.
The Fundamental Challenge:
A hotel sells perishable inventory. Unlike physical goods that can be stored indefinitely, a hotel room on January 15th that goes unsold is revenue lost forever—it cannot be "stored" for later sale. This creates intense pressure on:
Understanding that hotel inventory is perishable fundamentally shapes design decisions. Unlike an e-commerce system where a product either exists or doesn't, every room exists in a temporal context—available on specific dates, for specific durations. This makes room quantity tracking a multi-dimensional problem rather than simple counting.
Key Domain Concepts:
Before we can design, we must internalize the language of the domain:
| Aspect | Traditional Inventory | Hotel Inventory |
|---|---|---|
| Nature | Physical items, persistent | Time-bounded, perishable |
| Quantity | Single count (in stock or not) | Multi-dimensional (per date, per room type) |
| Pricing | Relatively static | Highly dynamic (demand, season, events) |
| Allocation | FIFO/LIFO/specific unit | Date-based, flexible assignment |
| Overbooking | Generally not applicable | Strategic business practice |
| Modifications | Order changes | Date changes, room type changes, extensions |
A robust requirements analysis identifies all stakeholders and their distinct needs. Each stakeholder interacts with the system differently, and failing to account for any perspective leads to incomplete designs.
Primary Stakeholders:
Stakeholders often have conflicting interests. Guests want flexibility (free cancellations); Revenue Managers want commitment (non-refundable rates). Front desk wants simple operations; Administrators want policy enforcement. Your design must accommodate these tensions through configuration and business rules, not hard-coded assumptions.
Functional requirements define what the system must do. For a hotel booking system, these span multiple complex workflows. Let's analyze each requirement category exhaustively.
The search functionality is deceptively complex. A seemingly simple query—"Find available rooms for 2 guests, March 15-18"—triggers multi-dimensional logic:
Core Search Requirements:
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// Conceptual search query structureinterface SearchQuery { // Temporal parameters checkInDate: Date; checkOutDate: Date; // Guest parameters adults: number; children: number; childAges?: number[]; // Room preferences roomTypePreference?: RoomType[]; amenityRequirements?: Amenity[]; accessibilityNeeds?: AccessibilityFeature[]; // Pricing context ratePlanCode?: string; promotionCode?: string; loyaltyTier?: LoyaltyTier; // Sorting/filtering sortBy?: 'price' | 'roomType' | 'rating'; priceRange?: { min: number; max: number };} interface SearchResult { roomType: RoomType; availableCount: number; rates: NightlyRate[]; totalPrice: Money; cancellationPolicy: CancellationPolicy; promotionsApplied: Promotion[];}A room must be available for ALL nights of a stay, not just some. If a guest wants March 15-18, the room must be available on the 15th, 16th, AND 17th nights. A common mistake is checking each night independently without ensuring continuous availability—leading to impossible reservations.
Reservations transition through well-defined states. Understanding this lifecycle is critical for correct implementation:
Reservation States:
Modifications to existing reservations trigger cascading logic:
Date Modifications:
Room Modifications:
Guest Modifications:
| Modification Type | Availability Check | Repricing Required | Policy Applied | History Record |
|---|---|---|---|---|
| Extend Stay | Yes (new nights) | Yes (new nights at current rates) | No | Yes |
| Shorten Stay | No | Yes (refund calculation) | Cancellation policy may apply | Yes |
| Date Shift | Yes (entire new range) | Yes (complete repricing) | Depends on policy | Yes |
| Room Upgrade | Yes (new room type) | Yes (rate difference) | No | Yes |
| Room Downgrade | Yes (new room type) | Yes (refund possible) | Depends on policy | Yes |
| Add Guests | No (capacity check only) | Maybe (extra person charges) | No | Yes |
Cancellation policies are among the most business-critical and complex aspects of hotel booking systems. They directly impact revenue, guest satisfaction, and operational planning.
Policy Dimensions:
Cancellation policies vary across multiple dimensions, and your system must handle all combinations:
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// Cancellation policy structureinterface CancellationPolicy { id: string; name: string; // e.g., "24-Hour Flexible", "Non-Refundable" tiers: CancellationTier[]; applicableRatePlans: string[]; seasonalOverrides?: SeasonalPolicyOverride[];} interface CancellationTier { // Hours before check-in when this tier applies hoursBeforeCheckin: number; // Penalty as percentage of total (0-100) penaltyPercentage: number; // Or fixed amount penalty fixedPenalty?: Money; // Nights charged as penalty nightsCharged?: number;} // Example: Standard Flexible Policyconst flexiblePolicy: CancellationPolicy = { id: "FLEX-001", name: "24-Hour Flexible", tiers: [ { hoursBeforeCheckin: 24, penaltyPercentage: 0 }, // Free cancellation { hoursBeforeCheckin: 0, penaltyPercentage: 100 } // Full charge ], applicableRatePlans: ["RACK", "BAR", "AAA", "CORP"]}; // Example: Non-Refundable Policyconst nonRefundablePolicy: CancellationPolicy = { id: "NR-001", name: "Non-Refundable", tiers: [ { hoursBeforeCheckin: Infinity, penaltyPercentage: 100 } // Always 100% ], applicableRatePlans: ["ADVANCE", "PACKAGE", "PROMO"]};Refund calculations must account for: partial payments already received, different rates on different nights (weekend vs. weekday), taxes calculated on the cancelled portion, loyalty points earned that must be reversed, and promotional discounts that may need recalculation. Never assume refund = total - penalty; the reality is more nuanced.
Non-functional requirements define how the system must perform. For a hotel booking system, these are equally important as functional requirements and heavily influence architectural decisions.
The absolute #1 reliability requirement: NEVER double-book a physical room. Two guests should never arrive expecting the same room on the same night. This requires careful concurrency handling, exactly-once semantics for booking confirmations, and robust distributed locking if applicable. Design violations here have immediate, visible business consequences.
Production systems encounter countless edge cases. Anticipating these during requirements analysis prevents painful redesigns later. Here are critical scenarios your design must handle:
| Scenario | Complexity | Handling Strategy |
|---|---|---|
| Same-day booking | Medium | Check current time vs. hotel's check-in cutoff; different availability logic |
| Multi-room booking | High | Atomic allocation of all rooms or none; partial availability handling |
| Cross-midnight check-in | Medium | Define clear cutoff times; late arrival notes; next-day date handling |
| Extended stay modification | High | Check availability for new nights; maintain room continuity preference |
| Rate change during stay | Medium | Rate lock policies; daily rate granularity vs. blended rate |
| Overbooking walk | High | Guest relocation process; compensation calculation; partner hotel integration |
| Room type unavailable | Medium | Upgrade/downgrade logic; rate adjustment; guest notification |
| Payment failure post-confirm | High | Reservation hold period; retry logic; eventual cancellation |
| Group block partial release | High | Block management; individual pickup tracking; cutoff date logic |
| Connecting rooms | Medium | Room relationship mapping; availability as unit; split booking handling |
Time-related edge cases deserve special attention:
Timezone Considerations:
Date Boundary Cases:
While dozens of edge cases exist, focus your initial design on the most impactful ones. A robust design handles the common 80% elegantly and provides extension points for the remaining 20%. Don't let edge case complexity paralyze your core design, but do document them for future implementation.
A hotel booking system doesn't operate in isolation. It must integrate with numerous external systems, each bringing interface requirements and constraints.
Design your core domain objects to be integration-agnostic. The Room, Reservation, and Guest entities shouldn't know whether data comes from Booking.com or your direct website. Use adapters and anti-corruption layers to translate between external formats and your clean domain model. This makes adding new channels trivial.
We've conducted a thorough requirements analysis for the Hotel Booking System. Let's consolidate our findings into a structured checklist that will guide design decisions:
What's Next:
With a solid understanding of requirements, we're ready to identify and design the core entities that will form our domain model. The next page will systematically extract and define Hotel, Room, Reservation, Guest, and supporting entities—establishing the building blocks for our object-oriented design.
You now have comprehensive requirements for a Hotel Booking System. This analysis reveals that hotel booking is far more complex than it appears—involving temporal inventory, intricate business rules, multiple stakeholders, and critical reliability constraints. The design we build must respect these realities.