The modeling, analysis and performance evaluation of large-scale systems are difficult tasks. 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 (e.g., logics) are used to express properties, which are automatically estimated again simulating the model at hand. These property specification languages provide a formal, compact and elegant way to express properties without hard-coding them in the model definition. This paper presents MultiVeStA, a statistical analysis tool which can be easily integrated with discrete event simulators, enriching them with efficient distributed statistical analysis and SMC capabilities.

MultiVeStA: Statistical model checking for discrete event simulators

Vandin A
2013-01-01

Abstract

The modeling, analysis and performance evaluation of large-scale systems are difficult tasks. 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 (e.g., logics) are used to express properties, which are automatically estimated again simulating the model at hand. These property specification languages provide a formal, compact and elegant way to express properties without hard-coding them in the model definition. This paper presents MultiVeStA, a statistical analysis tool which can be easily integrated with discrete event simulators, enriching them with efficient distributed statistical analysis and SMC capabilities.
2013
978-193696848-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11382/534318
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