arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1301.3299cs.LO
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符号模型检验的保反例约简

Counterexample-Preserving Reduction for Symbolic Model Checking

Wanwei Liu, Rui Wang, Xianjin Fu, Ji Wang, Wei Dong, Xiaoguang Mao

摘要:

LTL模型检验的成本对验证公式的长度高度敏感。我们观察到,在某些特定的条件下,输入LTL公式可以减少到一个制造商到处理之前的模型检验。在我们的约简中,这两个公式不需要在逻辑上等价,但它们在模型中共享相同的反例集。在模型被象征性地表示的情况下,能够以轻量级的努力(例如,解决问题)。在本文中,我们尝试将这种技术命名为“反例保持约简”(简称CePRe),最后通过采用NuSMV对所提出的技术进行了实验评估。

英文摘要:

The cost of LTL model checking is highly sensitive to the length of the formula under verification. We observe that, under some specific conditions, the input LTL formula can be reduced to an easier-to-handle one before model checking. In our reduction, these two formulae need not to be logically equivalent, but they share the same counterexample set w.r.t the model. In the case that the model is symbolically represented, the condition enabling such reduction can be detected with a lightweight effort (e.g., with SAT-solving). In this paper, we tentatively name such technique "Counterexample-Preserving Reduction" (CePRe for short), and finally the proposed technquie is experimentally evaluated by adapting NuSMV.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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