PhD scholarship in Automated Software Testing

This project aims to improve the software testing process for both traditional and AI-based systems. Its primary objectives include developing tools and techniques to enhance testing effectiveness while optimizing energy consumption and time efficiency. Software testing is a crucial phase of the Software Engineering process, often accounting for a significant portion of project budgets due to the effort required for manual test generation. This research investigates automated testing techniques to enhance the effectiveness and efficiency of the testing process. It also aims to propose novel metrics and performance criteria to evaluate the reliability of AI-based systems, for which traditional metrics like coverage and mutation score is infeasible. Additionally, the project explores 'green' testing strategies to optimize energy consumption, making the testing process more sustainable.