Compositional Analysis of Probabilistic Timed Graph Transformation Systems

Compositional Analysis of Probabilistic Timed Graph Transformation Systems
Author :
Publisher : Universitätsverlag Potsdam
Total Pages : 60
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ISBN-10 : 9783869565019
ISBN-13 : 3869565012
Rating : 4/5 (012 Downloads)

Book Synopsis Compositional Analysis of Probabilistic Timed Graph Transformation Systems by : Maria Maximova

Download or read book Compositional Analysis of Probabilistic Timed Graph Transformation Systems written by Maria Maximova and published by Universitätsverlag Potsdam. This book was released on 2022-05-19 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis of behavioral models is of high importance for cyber-physical systems, as the systems often encompass complex behavior based on e.g. concurrent components with mutual exclusion or probabilistic failures on demand. The rule-based formalism of probabilistic timed graph transformation systems is a suitable choice when the models representing states of the system can be understood as graphs and timed and probabilistic behavior is important. However, model checking PTGTSs is limited to systems with rather small state spaces. We present an approach for the analysis of large scale systems modeled as probabilistic timed graph transformation systems by systematically decomposing their state spaces into manageable fragments. To obtain qualitative and quantitative analysis results for a large scale system, we verify that results obtained for its fragments serve as overapproximations for the corresponding results of the large scale system. Hence, our approach allows for the detection of violations of qualitative and quantitative safety properties for the large scale system under analysis. We consider a running example in which we model shuttles driving on tracks of a large scale topology and for which we verify that shuttles never collide and are unlikely to execute emergency brakes. In our evaluation, we apply an implementation of our approach to the running example.


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