GigMatch Pro is a high-performance, algorithmic simulation engine for a freelance marketplace. Inspired by the gig economy logic, this system handles real-time user matching, dynamic skill evolution, and monthly simulation cycles for up to 500,000 users.

Unlike standard CRUD applications, this project implements custom data structures (Hash Tables and Priority Queues) from scratch to ensure $O(1)$ access times and efficient ranking algorithms without relying on built-in Java collections.

• Weighted Composite Ranking: Matches customers with the best freelancers using a multi-factor algorithm (Skill Match, Rating, Reliability).
• Dynamic Skill Evolution: Freelancers' skills grow with successful jobs and degrade with cancellations or inactivity.
• Burnout Mechanism: Simulates real-world fatigue; freelancers engaging in excessive workload suffer performance penalties.
• Loyalty System: Tier-based customer status (Bronze, Silver, Gold, Platinum) affecting pricing and platform subsidies.
• Automated Testing: Includes a custom Python script for batched input/output verification.

The core of GigMatch lies in its custom-built data structures designed for scalability:

• MyHashTable.java: A highly optimized hash table implementing separate chaining. It manages Customer and Freelancer objects, ensuring constant-time lookup even under heavy load (Test cases up to 500k operations).
• MyPriorityQueue.java: A binary heap implementation used to manage the Job Matching process. It allows the engine to instantly retrieve the highest-ranked freelancer based on the composite score.

• PlatformManager.java: The central controller that orchestrates user registration, job flow, monthly updates, and system-wide queries.
• Employment.java: Manages the lifecycle of a job, tracking state changes from "Hired" to "Completed" or "Cancelled".

The engine ranks freelancers for specific jobs using a weighted composite score formula:

• ** SkillScore: Dot product of freelancer skills and service requirements.
• ** Reliability: Impacted by cancellation rates.
• ** Burnout Penalty: Applied if a freelancer exceeds safe workload limits.

GigMatch-Engine/
├── src/
│   ├── Main.java              # Entry point
│   ├── PlatformManager.java   # Simulation controller
│   ├── Freelancer.java        # User model with skill vectors
│   ├── Customer.java          # User model with loyalty logic
│   ├── Employment.java        # Job transaction model
│   ├── MyHashTable.java       # Custom K-V store implementation
│   └── MyPriorityQueue.java   # Custom Heap implementation
├── test_cases/
│   ├── inputs/                # Large scale datasets
│   └── outputs/               # Expected simulation results
├── test_runner.py             # Automated Python testing script
└── README.md

A custom Python Test Runner (test_runner.py) was developed to validate the engine's accuracy against massive datasets.

• Function: Automatically executes the compiled Java bytecode against input files.
• Validation: Compares the generated output with expected logs line-by-line.
• Performance: Measures execution time to ensure the custom data structures meet the required time complexity constraints.

Compile the Project:

javac src/*.java
Run the Simulation:

java Main input.txt output.txt
Run the Test Suite (Python):

python3 tests/test_runner.py

Developed by Melih Efe Sonmez.