Domain Adaptation for Code Model-based Unit Test Case Generation

Understand

Recently, deep learning-based test case generation approaches have been proposed to automate the generation of unit test cases.

• In this study, we leverage Transformer-based code models to generate unit tests with the help of Domain Adaptation (DA) at a project level.
• Specifically, we use CodeT5, a relatively small language model trained on source code data, and fine-tune it on the test generation task.
• Then, we apply domain adaptation to each target project data to learn project-specific knowledge (project-level DA).