A bounded statistical approach for model checking of unbounded until properties

Ru He, Paul Jennings, Samik Basu, Arka P. Ghosh, Huaiqin Wu
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引用次数: 19

Abstract

We study the problem of statistical model checking of probabilistic systems for PCTL unbounded until property PJoinp(Æ1UÆ2) (where Join |X| {<, d, >, e}) using the computation of P d 0(Æ1UÆ2). The approach is first proposed by Sen et al. in CAV'05 but their approach suffers from two drawbacks. Firstly, the computation of Pd0Æ1UÆ2) requires for its validity, a user-specified input parameter ´2 which the user is unlikely to correctly provide. Secondly, the validity of computation of Pd0Æ1UÆ2) is limited only to probabilistic models that do not contain loops. We present a new technique which addresses both problems described above. Essentially our technique transforms the hypothesis test for the unbounded until property in the original model into a new equivalent hypothesis test for bounded until property in our modified model. We empirically show the effectiveness of our technique and compare our results with those using the method proposed by Sen et al.
无界until属性模型检验的有界统计方法
利用P d 0(Æ1UÆ2)的计算,研究了PCTL无界直到属性PJoinp(Æ1UÆ2)(其中Join |X| {, e})的概率系统的统计模型检验问题。该方法首先由Sen等人在CAV'05中提出,但他们的方法存在两个缺点。首先,Pd0Æ1UÆ2)的计算需要用户指定的输入参数´2来保证其有效性,而用户不太可能正确提供该参数。其次,Pd0Æ1UÆ2)计算的有效性仅限于不包含循环的概率模型。我们提出了一种解决上述两个问题的新技术。本质上,我们的技术将原始模型中无界直到属性的假设检验转换为修改模型中有界直到属性的新的等效假设检验。我们通过经验证明了我们的技术的有效性,并将我们的结果与Sen等人提出的方法进行了比较。
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