CPSDebug: Automatic failure explanation in CPS models

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 bef...

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Vydané v:International journal on software tools for technology transfer Ročník 23; číslo 5; s. 783 - 796
Hlavní autori: Bartocci, Ezio, Manjunath, Niveditha, Mariani, Leonardo, Mateis, Cristinel, Ničković, Dejan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2021
Springer Nature B.V
Predmet:
Computer Science
Continuity (mathematics)
Cyber-physical systems
Failure analysis
Software Engineering
Software Engineering/Programming and Operating Systems
State machines
Theory of Computation
Cyber-physical systems
Failure explanation
Model-based development
Property mining
Debugging
Testing
ISSN:1433-2779, 1433-2787
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1433-2779
1433-2787
DOI:10.1007/s10009-020-00599-4