ARCH-COMP18 Category Report

Stochastic Modelling

Conference Paper (2018)
Authors

Alessandro Abate (University of Oxford)

Henk A.P. Blom (Air Transport & Operations)

Nathalie Cauchi (University of Oxford)

Sofie Haesaert (California Institute of Technology)

Arnd Hartmanns (University of Twente)

Kendra Lesser (Verus Research)

Meeko Oishi (University of New Mexico)

Vignesh Sivaramakrishnan (University of New Mexico)

Sadegh Soudjani (Newcastle University)

G.B. More Authors (External organisation)

Research Group
Air Transport & Operations
Copyright
© 2018 Alessandro Abate, H.A.P. Blom, Nathalie Cauchi, Sofie Haesaert, Arnd Hartmanns, Kendra Lesser, Meeko Oishi, Vignesh Sivaramakrishnan, Sadegh Soudjani, More Authors
To reference this document use:
https://doi.org/10.29007/7ks7
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 Alessandro Abate, H.A.P. Blom, Nathalie Cauchi, Sofie Haesaert, Arnd Hartmanns, Kendra Lesser, Meeko Oishi, Vignesh Sivaramakrishnan, Sadegh Soudjani, More Authors
Research Group
Air Transport & Operations
Volume number
54
Pages (from-to)
71-103
DOI:
https://doi.org/10.29007/7ks7
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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 favours. 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.

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