Abstract-This tool paper introduces COSMOS, a statistical model checker for the Hybrid Automata Stochastic Logic (HASL). HASL employs Linear Hybrid Automata (LHA), a generalization of Deterministic Timed Automata (DTA), to describe accepting execution paths of a Discrete Event Stochastic Process (DESP), a class of stochastic models which includes, but is not limited to, Markov chains. As a result HASL verification turns out to be a unifying framework where sophisticated temporal reasoning is naturally blended with elaborate reward-based analysis. COSMOS takes as input a DESP (described in terms of a Generalized Stochastic Petri Net), an LHA and an expression Z representing the quantity to be estimated. It returns a confidence interval estimation of Z. COSMOS is written in C++ and is freely available to the research community.
We introduce the Hybrid Automata Stochastic Logic (HASL), a new temporal logic formalism for the verification of discrete event stochastic processes (DESP). HASL employs Linear Hybrid Automata (LHA) as machineries to select prefixes of relevant execution paths of a DESP D. The advantage with LHA is that rather elaborate information can be collected on-the-fly during path selection, providing the user with a powerful means to express sophisticated measures. A formula of HASL consists of an LHA A and an expression Z referring to moments of path random variables. A simulation-based statistical engine is employed to obtained a confidence-interval estimate of the expected value of Z. In essence HASL provide a unifying verification framework where sophisticated temporal reasoning is naturally blended with elaborate reward-based analysis. We illustrate the HASL approach by means of some examples and a discussion about its expressivity. We also provide empirical evidence obtained through COSMOS, a prototype software tool for HASL verification.
International audienceWe introduce the Hybrid Automata Stochastic Language (HASL), a new temporal logic formalism for the verification of Discrete Event Stochastic Processes (DESP). HASL employs a Linear Hybrid Automaton (LHA) to select prefixes of relevant execution paths of a DESP. LHA allows rather elaborate information to be collected on-the-fly during path selection, providing the user with powerful means to express sophisticated measures. A formula of HASL consists of an LHA and an expression Z referring to moments of path random variables. A simulation-based statistical engine is employed to obtain a confidence interval estimate of the expected value of Z. In essence, HASL provides a unifying verification framework where temporal reasoning is naturally blended with elaborate reward-based analysis. Moreover, we have implemented a tool, named COSMOS, for performing analysis of HASL formula for DESP modelled by Petri nets. Using this tool we have developed two detailed case studies: a flexible manufacturing system and a genetic oscillator
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.