Mutahunter
Mutahunter is an innovative open-source tool designed for mutation testing across multiple programming languages, leveraging Large Language Model (LLM) technology like GPT-4o. It aims to enhance software quality by generating and testing code mutations to identify weaknesses in test suites.
Key Features
- Language Agnostic: Supports various programming languages, making it versatile for diverse development environments.
- LLM-Based Mutation Testing: Utilizes advanced AI models to create meaningful mutations, improving test coverage analysis.
- Customizable Testing: Allows users to specify source and test file paths, along with custom test commands (e.g.,
mvn clean testfor Java). - Detailed Reporting: Provides comprehensive mutation coverage statistics, including survived, killed, and timeout mutants, alongside cost estimation for API usage.
- Integration-Friendly: Easily integrates into existing workflows with simple installation via GitHub and command-line execution.
Use Cases
- Software Developers: Ideal for developers seeking to improve unit test effectiveness by identifying untested code paths.
- Quality Assurance Teams: Helps QA professionals ensure robust test suites through automated mutation testing.
- Educational Purposes: Useful in academic settings for teaching software testing concepts and practices.
- Enterprise Applications: Supports large-scale projects by providing insights into test suite quality, crucial for maintaining high standards in production code.
Mutahunter stands out with its AI-driven approach, offering a cost-effective ($0.00060 per run in examples) and powerful solution to enhance software reliability across industries.
