Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

11-2018

Abstract

Several schemes have been provided in Statistical Model Checking (SMC) for the estimation of property occurrence based on predefined confidence and absolute or relative error. Simulations might be however costly if many samples are required and the usual algorithms implemented in statistical model checkers tend to be conservative. Bayesian and rare event techniques can be used to reduce the sample size but they can not be applied without prerequisite or knowledge about the system under scrutiny. Recently, sequential algorithms based on Monte Carlo estimations and Massart bounds have been proposed to reduce the sample size while providing guarantees on error bounds which has been shown to outperform alternative frequentist approaches [15]. In this work, we discuss some features regarding the distribution and the optimisationof these algorithms.

Keywords

Error analysis, formal methods

Discipline

Software Engineering | Theory and Algorithms

Research Areas

Software and Cyber-Physical Systems

Publication

Leveraging Applications of Formal Methods, Verification and Validation: 8th International Symposium ISoLA 2018, Limasso, Cyprus, October 30 - November 13

Volume

11245

First Page

287

Last Page

304

ISBN

9783030034214

Identifier

10.1007/978-3-030-03421-4_19

Publisher

Springer

City or Country

Cham

Additional URL

https://doi.org/10.1007/978-3-030-03421-4_19

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