LLM-Test-Generator

Goal

Testing code thoroughly requires substantial time and effort. Companies with limited resources often struggle to create high-quality tests, resulting in issues in the production environment. This proof of concept was made to see if we can use a Large Language Model to generate unit tests for arbitrary source code. This POC focuses on java unit tests.

⚠️ Please be aware, at this point, this has produced results that are reasonably close to quality tests, but still needs manual intervention. ⚠️

Setup

Tools:

• Maven
• gcloud cli
  • Google Cloud Project with Vertex AI enabled
• SonarQube
  • Add the corresponding bin folder to the path (e.g - sonarqube-10.0.0.68432/bin/macosx-universal-64/)
  • Add credentials as environment variables SONAR_USER and SONAR_PASS

Running

To run this - Use python3 test_generator.py <git_url> Optional - use --module=<module_path> (relative to the target repository root) to make the generation set smaller

Viewing Results

The generated tests can be found in the test folders of their corresponding modules in the target repository. They will be named <Source File Name>GenTest.java You can find the final prompts for each of the methods in final_prompts once they have been prepared You may need to make manual edits, but it is still faster than writing the tests from scratch