| Title | Six Software Engineering Principles for Smarter Cyber-Physical Systems |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Weyns, Danny, Bures, Tomas, Calinescu, Radu, Craggs, Barnaby, Fitzgerald, John, Garlan, David, Nuseibeh, Bashar, Pasquale, Liliana, Rashid, Awais, Ruchkin, Ivan, Schmerl, Bradley |
| Conference Name | 2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C), Proceedings of the Workshop on Self-Improving System Integration |
| Date Published | 09/2021 |
| Conference Location | Washington, DC |
| Keywords | 2021: October, CMU |
| Abstract | Cyber-Physical Systems (CPS) integrate computational and physical components. With the digitisation of society and industry and the progressing integration of systems, CPS need to become “smarter” in the sense that they can adapt and learn to handle new and unexpected conditions, and improve over time. Smarter CPS present a combination of challenges that existing engineering methods have difficulties addressing: intertwined digital, physical and social spaces, need for heterogeneous modelling formalisms, demand for context-tied cooperation to achieve system goals, widespread uncertainty and disruptions in changing contexts, inherent human constituents, and continuous encounter with new situations. While approaches have been put forward to deal with some of these challenges, a coherent perspective on engineering smarter CPS is lacking. In this paper, we present six engineering principles for addressing the challenges of smarter CPS. As smarter CPS are software-intensive systems, we approach them from a software engineering perspective with the angle of self-adaptation that offers an effective approach to deal with run-time change. The six principles create an integrated landscape for the engineering and operation of smarter CPS. |
| DOI | 10.1109/ACSOS-C52956.2021.00058 |
| Citation Key | node-81234 |
Six Software Engineering Principles for Smarter Cyber-Physical Systems