## Statistical Model Checking of Black-Box Probabilistic Systems (2004)

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Venue: | In 16th conference on Computer Aided Verification (CAV’04), volume 3114 of LNCS |

Citations: | 50 - 7 self |

### BibTeX

@INPROCEEDINGS{Sen04statisticalmodel,

author = {Koushik Sen and Mahesh Viswanathan and Gul Agha},

title = {Statistical Model Checking of Black-Box Probabilistic Systems},

booktitle = {In 16th conference on Computer Aided Verification (CAV’04), volume 3114 of LNCS},

year = {2004},

pages = {202--215},

publisher = {Springer}

}

### Years of Citing Articles

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### Abstract

We propose a new statistical approach to analyzing stochastic systems against specifications given in a sublogic of continuous stochastic logic (CSL). Unlike past numerical and statistical analysis methods, we assume that the system under investigation is an unknown, deployed black-box that can be passively observed to obtain sample traces, but cannot be controlled. Given a set of executions (obtained by Monte Carlo simulation) and a property, our algorithm checks, based on statistical hypothesis testing, whether the sample provides evidence to conclude the satisfaction or violation of a property, and computes a quantitative measure (p-value of the tests) of confidence in its answer; if the sample does not provide statistical evidence to conclude the satisfaction or violation of the property, the algorithm may respond with a "don't know" answer. We implemented our algorithm in a Java-based prototype tool called VeStA, and experimented with the tool using case studies analyzed in [15]. Our empirical results show that our approach may, at least in some cases, be faster than previous analysis methods.

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