Sandra Greiner, Klaus Schmid, Thorsten Berger, Sebastian Krieter, Kristof Meixner
Technical Track
 | Haus der Universität, Schlösslistrasse 5, 3008 Bern, Switzerland |
 | 9 February 2024, 11:30 CET |
 | Sandra Greiner |
 | Mathieu Acher |
 | https://dl.acm.org/doi/10.1145/3634713.3634722 |
Generative Artificial Intelligence (GAI) promises groundbreaking automation technology – a potential which may raise the management of variability-intensive software systems to a new level of automation. Several activities in maintaining variability-intensive software systems, such as extracting feature traces to updating features consistently, are repetitive and performed mainly manually or semi-automatically. Exploiting the potentials of GAI in maintaining variability-intensive software systems opens a fundamentally new research perspective, where GAI shall solve repetitive and hard-to-automate tasks. In this vision paper, we propose and discuss increasing levels of maintaining variability-intensive software systems automatically enabled through the support of GAI. We sketch actions necessary to reach the next levels of automation while discussing the current state-of-the-art.