Towards a Holistic Software Systems Engineering Approach for Dependable Autonomous Systems
Title | Towards a Holistic Software Systems Engineering Approach for Dependable Autonomous Systems |
Publication Type | Conference Paper |
Year of Publication | 2018 |
Authors | Aniculaesei, Adina, Grieser, Jörg, Rausch, Andreas, Rehfeldt, Karina, Warnecke, Tim |
Conference Name | Proceedings of the 1st International Workshop on Software Engineering for AI in Autonomous Systems |
Date Published | May 2018 |
Publisher | ACM |
ISBN Number | 978-1-4503-5739-5 |
Keywords | Autonomic Security, autonomous systems, composability, Dependability, privacy, pubcrawl, quality assurance, resilience, Resiliency, runtime verification, Safety, security, self-learning systems |
Abstract | Autonomous systems are gaining momentum in various application domains, such as autonomous vehicles, autonomous transport robotics and self-adaptation in smart homes. Product liability regulations impose high standards on manufacturers of such systems with respect to dependability (safety, security and privacy). Today's conventional engineering methods are not adequate for providing guarantees with respect to dependability requirements in a cost-efficient manner, e.g. road tests in the automotive industry sum up millions of miles before a system can be considered sufficiently safe. System engineers will no longer be able to test and respectively formally verify autonomous systems during development time in order to guarantee the dependability requirements in advance. In this vision paper, we introduce a new holistic software systems engineering approach for autonomous systems, which integrates development time methods as well as operation time techniques. With this approach, we aim to give the users a transparent view of the confidence level of the autonomous system under use with respect to the dependability requirements. We present already obtained results and point out research goals to be addressed in the future. |
URL | https://dl.acm.org/doi/10.1145/3194085.3194091 |
DOI | 10.1145/3194085.3194091 |
Citation Key | aniculaesei_towards_2018 |