Automated Test Case Generation in a Real-World System Using a Customized AI Agent: An Experience Report - Lima, Gabrielle; Silva, Diógenes; Mar, Carlos; Coronel, Diego (Anais do Simpósio Brasileiro de Qualidade de Software (SBQS); 2025: Anais do XXIV Simpósio Brasileiro de Qualidade de SoftwareDO - 10.5753/sbqs.2025.15010, 2025)
Test case design is an essential activity in software quality assurance. However, when performed manually, it can be time-consuming, error-prone, and require substantial effort, particularly in complex applications. This experience report describes the development and application of an artificial intelligence agent, built using the ChatGPT platform, designed to automate the process of generating test cases for a real-world system and reduce the time required. The agent was configured to simulate the role of a QA analyst, using functional requirements, interface prototypes, and prompt engineering strategies to produce test scenarios with high coverage and accuracy. Experimentswere conducted on one of the modules of a component assembly control system, comparing manually created test cases with those generated by the agent. The results showed a reduction of over 50% in specification time while maintaining the quality and coverage of the scenarios. This paper details the agent’s configuration, the results achieved, the challenges encountered, and the lessons learned, contributing evidence for the practical use of generative AI in the context of software quality assurance.