Automated testing and other means for quality assurance are vital parts of any software endeavor. This topic for the theme was originally suggested by companies to enhance testing in continuous delivery cycles. The scene has changed with the rapid uptake of AI/ML technology for realizing software components as well as generating software with generative AI, such as LLMs. Experience and research show that these types of software do not always behave in the same way and have other dependencies compared to non-AI software which calls for new approaches of quality assurance. The development of such approaches is the focus of the theme as well as applying AI tools to the testing activities themselves. Critical systems demand human responsibility and research in the theme is also dealing with human-centered techniques to ensure transparent and explainable results. AI/ML has consequences beyond immediate use which motivates sustainability studies in the theme.

Overview of project proposals for theme 1, sprint 28