Reference : Automated Fault Tolerance Augmentation in Model-Driven Engineering for CPS
Scientific journals : Article
Engineering, computing & technology : Computer science
Security, Reliability and Trust
http://hdl.handle.net/10993/41575
Automated Fault Tolerance Augmentation in Model-Driven Engineering for CPS
English
Hu, Tingting mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Cibrario Bertolotti, Ivan [National Research Council of Italy > Institute of Electronics, Computer and Telecommunication Engineering]
Navet, Nicolas mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Havet, Lionel [RealTime-at-Work (RTaW)]
Jun-2020
Computer Standards and Interfaces
Elsevier
70
Yes (verified by ORBilu)
International
0920-5489
[en] Cognification ; Model-Driven Engineering ; Fault-tolerance ; Industrial Cyber Physical Systems ; Domain-Specific Languages
[en] Cyber-Physical Systems are usually subject to dependability requirements such as safety and reliability constraints. Over the last 50 years, a body of efficient fault-tolerance mechanisms has been devised to handle faults occurring at run-time. However, properly implementing those mechanisms is a time-consuming task that requires a great deal of know-how. In this paper, we propose a general framework which allows system designers to decouple functional and non-functional concerns, and express non- functional properties at design time using domain-specific languages. In the spirit of generative programming, functional models are then automatically “augmented” with dependability mechanisms. Importantly, the real-time behavior of the initial models in terms of sampling times and meeting deadlines is preserved. The practicality of the approach is demonstrated with the automated implementation of one prominent software fault-tolerance pattern, namely N-Version Programming, in the CPAL model-driven engineering workflow.
Researchers ; Professionals
http://hdl.handle.net/10993/41575
10.1016/j.csi.2020.103424
https://www.sciencedirect.com/science/article/abs/pii/S0920548919301710?via%3Dihub

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