MultiVeStA: Statistical Model Checking for Discrete Event Simulators. The modeling, analysis and performance evaluation of large-scale systems are difficult tasks. Due to the size and complexity of the considered systems, an approach typically followed by engineers consists in performing simulations of systems models to obtain statistical estimations of quantitative properties. Similarly, a technique used by computer scientists working on quantitative analysis is Statistical Model Checking (SMC), where rigorous mathematical languages (typically logics) are used to express systems properties of interest. Such properties can then be automatically estimated by tools performing simulations of the model at hand. These property specifications languages, often not popular among engineers, provide a formal, compact and elegant way to express systems properties without needing to hard-code them in the model definition. This paper presents MultiVeStA, a statistical analysis tool which can be easily integrated with existing discrete event simulators, enriching them with efficient distributed statistical analysis and SMC capabilities.
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References in zbMATH (referenced in 4 articles )
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- Maggi, Alessandro; Petrocchi, Marinella; Spognardi, Angelo; Tiezzi, Francesco: A language-based approach to modelling and analysis of Twitter interactions (2017)
- ter Beek, Maurice H.; Fantechi, Alessandro; Gnesi, Stefania; Mazzanti, Franco: Modelling and analysing variability in product families: model checking of modal transition systems with variability constraints (2016)
- Belzner, Lenz; De Nicola, Rocco; Vandin, Andrea; Wirsing, Martin: Reasoning (on) service component ensembles in rewriting logic (2014) ioport
- Bruni, Roberto; Corradini, Andrea; Gadducci, Fabio; Lluch Lafuente, Alberto; Vandin, Andrea: Modelling and analyzing adaptive self-assembly strategies with Maude (2012) ioport