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Enhanced Vacuity Detection in Linear Temporal Logic

机译:增强了线性时间逻辑中的真空检测

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One of the advantages of temporal-logic model-checking tools is their ability to accompany a negative answer to a correctness query with a counterexample to the satisfaction of the specification in the system. On the other hand, when the answer to the correctness query is positive, most model-checking tools provide no witness for the satisfaction of the specification. In the last few years there has been growing awareness of the importance of suspecting the system or the specification of containing an error also in cases where model checking succeeds. In particular, several works have recently focused on the detection of the vacuous satisfaction of temporal logic specifications. For example, when verifying a system with respect to the specification ψ = G(rep → Fgrant) ("every request is eventually followed by a grant"), we say that ψ is satisfied vacuously in systems in which requests are never sent. Current works have focused on detecting vacuity with respect to subformula occurrences. In this work we investigate vacuity detection with respect to subformulas with multiple occurrences. The generality of our framework requires us to re-examine the basic intuition underlying the concept of vacuity, which until now has been defined as sensitivity with respect to syntactic perturbation. We study sensitivity with respect to semantic perturbation, which we model by universal propositional quantification. We show that this yields a hierarchy of vacuity notions. We argue that the right notion is that of vacuity defined with respect to traces. We then provide an algorithm for vacuity detection and discuss pragmatic aspects.
机译:一个时空逻辑模型检查工具的优势是他们陪了否定的回答正确性查询与反例在系统中规范的满意度的能力。在另一方面,当答案的正确性查询是肯定的,大多数模型检测工具提供了规范的满意度没有证人。在过去的几年里一直是怀疑的系统或包含错误也会在模型检验成功的情况下该规范的重要性的认识不断提高。特别是,几部作品最近集中在检测的时序逻辑规格空洞的满意度。例如,验证系统相对于所述规范ψ= G(REP→Fgrant)(“每一个请求最终后跟一个金”)时,我们就说ψ在其中请求永远不会发送系统空洞地满足。当前工作的重点是相对于子公式出现检测空白。在这项工作中,我们调查虚标检测方面,拥有多个分身子公式。我们的框架的一般性要求我们重新审视了基本的直觉真空度的概念,到现在为止已经相对于语法扰动定义为潜在的敏感性。我们对于语义扰动,这是我们的普遍命题量化模型研究的敏感性。我们表明,这种产生真空概念的层次结构。我们认为,正确的观念是相对于痕迹定义虚标。然后,我们提供了虚标检测的算法,并讨论务实的方面。

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