MultiVeStA: Statistical model checking for discrete event simulators

Stefano Sebastio*, Andrea Vandin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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 Multi Ve St A, a statistical analysis tool which can be easily integrated with discrete event simulators, enriching them with efficient distributed statistical analysis and SMC capabilities.

Original languageEnglish
Title of host publicationVALUETOOLS 2013 - 7th International Conference on Performance Evaluation Methodologies and Tools
Number of pages6
PublisherICST
Publication date2013
Pages310-315
ISBN (Electronic)9781936968480
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event7th International Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2013 - Torino, Italy
Duration: 10 Dec 201312 Dec 2013

Conference

Conference7th International Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2013
CountryItaly
CityTorino
Period10/12/201312/12/2013

Keywords

  • Discrete event simulation
  • Quantitative analysis
  • Statistical analysis
  • Statistical model checking

Cite this

Sebastio, S., & Vandin, A. (2013). MultiVeStA: Statistical model checking for discrete event simulators. In VALUETOOLS 2013 - 7th International Conference on Performance Evaluation Methodologies and Tools (pp. 310-315). ICST. https://doi.org/10.4108/icst.valuetools.2013.254377