Gator Ticket Master

Author: Divyam Dubey

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Project Overview

The Gator Ticket Master system streamlines seat reservations for Gator events, automating processes like seat allocation, cancellations, and waitlist management. The system:

• Manages seat reservations dynamically, adding seats as demand increases.
• Prioritizes users on the waitlist based on priority and earliest request timestamps.
• Cancels reservations and efficiently reallocates seats.
• Detects and handles unusual activity with administrative seat releases.

Key Features

1. Seat Assignment: Allocates seats in ascending order.
2. Waitlist Management: Maintains a priority-based waitlist for users.
3. Dynamic Seat Allocation: Adds seats dynamically based on demand.
4. Admin Control: Supports bulk seat releases in cases of unusual activity.

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Project Structure

Main Components

• gatorTicketMaster.py: Handles user interactions and implements core functions.
• BinaryHeap.py: Manages unassigned seat IDs.
• RedBlackTree.py: Tracks active reservations efficiently.
• WaitlistMaxBinaryHeap.py: Manages the priority-based waitlist.

Core Functions

1. Initialize(seatCount: int): Sets up the initial seating arrangement.
2. Reserve(userId: int, userPriority: int): Reserves a seat or adds the user to the waitlist.
3. Cancel(seatId: int, userId: int): Cancels a reservation and reassigns the seat if needed.
4. Available(): Displays current seat availability and waitlist status.
5. ExitWaitlist(userId: int): Removes a user from the waitlist.
6. UpdatePriority(userId: int, userPriority: int): Updates a user’s priority in the waitlist.
7. AddSeats(count: int): Adds new seats to the system and assigns them to waitlisted users.
8. PrintReservations(): Lists all current reservations.
9. ReleaseSeats(userId1: int, userId2: int): Cancels reservations within a range of user IDs.
10. Quit(): Ends the program execution.

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Key Data Structures

Binary Heap (Min Heap)

• Purpose: Stores unassigned seats.
• Complexity: O(log n) for insertions and minimum extraction.
• Key Methods:
  • insert(item)
  • extract_min()
  • remove_arbitrary(item)

Red-Black Tree

• Purpose: Manages active reservations.
• Complexity: O(log n) for search, insertion, and deletion.
• Key Methods:
  • insert(key, seatId)
  • delete(key)
  • search(key)
  • inorder_traversal()

Max Binary Heap

• Purpose: Manages the waitlist with priority-based ordering.
• Complexity: O(log n) for insertions and maximum extraction.
• Key Methods:
  • insert(userId, priority, timestamp)
  • extract_max()
  • update_priority(userId, new_priority)
  • remove_user(userId)

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Data Flow

1. Input Processing: Reads commands from an input file and executes corresponding functions.
2. Seat Management: Tracks unassigned and reserved seats using the Binary Heap and Red-Black Tree.
3. Waitlist Management: Handles user priorities and timestamps with a Max Binary Heap.
4. Output Generation: Writes operation results to an output file.

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Implementation Details

Data Structures and Rationale

1. Binary Heap (Min Heap): Efficiently assigns the lowest available seat.
2. Red-Black Tree: Ensures fast operations for reservation management.
3. Max Binary Heap: Prioritizes waitlisted users based on priority and timestamps.

Additional Features

• Dynamic Seat Addition: Adds new seats and assigns them to waitlisted users.
• Timestamp Usage: Ensures fairness for users with equal priority.
• Batch Seat Release: Handles bulk cancellations or administrative actions.

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Time Complexity

Operation	Complexity
Initialize	O(n log n)
Reserve	O(log n)
Cancel	O(log n)
Available	O(1)
ExitWaitlist	O(log n)
UpdatePriority	O(log n)
AddSeats	O(m log n)
PrintReservations	O(n)
ReleaseSeats	O((k + m) log n)

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Space Complexity

• Binary Heap: Unassigned seats.
• Red-Black Tree: Active reservations.
• Max Binary Heap: Waitlist.

Overall: O(n), where n is the total number of seats.

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Usage

1. Run the program using the Python interpreter.
2. Input commands via a file to initialize and interact with the system.

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Performance Considerations

• Optimized for large-scale events using efficient data structures.
• Designed for dynamic seat additions and priority updates.

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Error Handling

• Validates inputs to prevent invalid operations.
• Handles edge cases like non-existent reservations and updates for non-waitlisted users.

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