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Publications in Scientific Journals:

E. Bartocci, N. Manjunath, L. Mariani, C. Mateis, D. Nickovic:
"CPSDebug: Automatic Failure Explanation in CPS Models";
accepted for publication in International Journal on Software Tools for Technology Transfer (2021).



English abstract:
Debugging cyber-physical system (CPS) models is a cumbersome and costly activity. CPS models combine continuous and discrete dynamics-a fault in a physical component manifests itself in a very different way than a fault in a state machine. Furthermore, faults can propagate both in time and space before they can be detected at the observable interface of the model. As a consequence, explaining the reason of an observed failure is challenging and often requires domain-specific knowledge. In this paper, we propose approach, a novel CPSDebug that combines testing, specification mining, and failure analysis, to automatically explain failures in Simulink/Stateflow models. In particular, we address the hybrid nature of CPS models by using different methods to infer properties from continuous and discrete state variables of the model. We evaluate CPSDebug on two case studies, involving two main scenarios and several classes of faults, demonstrating the potential value of our approach.


"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.1007/s10009-020-00599-4

Electronic version of the publication:
https://link.springer.com/article/10.1007/s10009-020-00599-4


Created from the Publication Database of the Vienna University of Technology.