PI: Nauman bin Ali (BTH), co-PI: Emelie Engström (LU); with Martin Höst (LU), Muhammad Usman (BTH), Jürgen Borstler, Claes Wohlin, Per Runeson, Kai Petersen
Software quality assurance includes preventive, diagnostic and corrective mechanisms to ensure the design and development of high-quality software systems. Advances in technology, like cloud computing and modern toolchains for automated builds, testing and deployment, have enabled organizations engaging in continuous software engineering to deploy a new version of a system ever more rapidly. This new way of working requires automation and puts new requirements in terms of the role and responsibilities of quality assurance.
In this project, we will explore the interaction between automated and manual data analysis in such contexts. We will investigate the use of data analytics and visualizations to help software engineers interpret the massive amount of data available due to activities like code analysis, version management, code reviews, testing and product usage. Furthermore, to support the integration of research activities and results in the industrial context, we will advance the work on improving the knowledge co-creation between industry and academia in software quality assurance.
Project number: B07