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ARCH-COMP18 Category Report: Stochastic Modelling

33 pagesPublished: September 17, 2018

Abstract

This report presents the results of a friendly competition for formal verification and policy synthesis of stochastic models. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in 2018. In this first edition, we present five benchmarks with different levels of complexities and stochastic flavours. We make use of six different tools and frameworks (in alphabetical order): Barrier Certificates, FAUST2, FIRM-GDTL, Modest, SDCPN modelling & MC simulation and SReachTools; and attempt to solve instances of the five different benchmark problems. Through these benchmarks, we capture a snapshot on the current state-of the art tools and frameworks within the stochastic modelling domain. We also present the challenges encountered within this domain and highlight future plans which will push forward the development of more tools and methodologies for performing formal verification and optimal policy synthesis of stochastic processes.

In: Goran Frehse (editor). ARCH18. 5th International Workshop on Applied Verification of Continuous and Hybrid Systems, vol 54, pages 71--103

Links:
BibTeX entry
@inproceedings{ARCH18:ARCH_COMP18_Category_Report_Stochastic,
  author    = {Alessandro Abate and Henk Blom and Nathalie Cauchi and Sofie Haesaert and Arnd Hartmanns and Kendra Lesser and Meeko Oishi and Vignesh Sivaramakrishnan and Sadegh Soudjani and Cristian-Ioan Vasile and Abraham P. Vinod},
  title     = {ARCH-COMP18 Category Report: Stochastic Modelling},
  booktitle = {ARCH18. 5th International Workshop on Applied Verification of Continuous and Hybrid Systems},
  editor    = {Goran Frehse},
  series    = {EPiC Series in Computing},
  volume    = {54},
  pages     = {71--103},
  year      = {2018},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {https://easychair.org/publications/paper/DzD8},
  doi       = {10.29007/7ks7}}
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