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

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