Authors - Heidi Koivisto, Sari Ahonen Abstract - The integration of AI-assisted code generation tools in software development has the potential to significantly improve productivity and code quality. This paper presents a comparative study of several leading AI tools, including GitHub Copilot, Amazon Q, GitLab Duo, and Claude Code, in the context of software quality assurance (QA). These tools are evaluated based on their ability to generate test cases for a sample application, focusing on metrics such as test coverage, accuracy, and maintainability. Our findings provide insights into the strengths and limitations of each tool, offering guidance to practitioners seeking to take advantage of AI in their QA processes. The results indicate that while AI tools can accelerate test case generation and improve coverage, careful consideration is needed to ensure the generated tests are relevant and maintainable in the long term.
Open Zoom