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arXiv 2109.04656cs.LO
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基于加强规范的模型检验的高效黑盒检验

Efficient Black-Box Checking via Model Checking with Strengthened Specifications

Junya Shijubo, Masaki Waga, Kohei Suenaga

摘要:

黑盒检查(BBC)是一种用于网络物理系统(CPS)以及软件系统的测试方法。BBC由主动自动机学习和模型检验组成;从被测系统(SUT)学习Mealy机,并使用模型检验针对规范验证学习的Mealy机。当Mealy机违反规范时,模型检查器返回一个输入,证明Mealy机违反规范。我们使用它来改进Mealy机或得出SUT违反规范的结论。否则,我们进行等价性测试,以找到一个输入见证的Mealy机和SUT之间的差异。在CPS的BBC中,由于系统执行的时间,等效性测试往往是耗时的。本文利用模型检验对BBC进行了改进,并加强了规范.通过加强规格说明的模型检验,我们有更多的机会获得一个输入见证规格说明违反比模型检验与原始规格说明。通过对Mealy机进行改进,可以减少等价性检验的次数,提高效率。我们用汽车基准进行了实验。实验结果证明了该方法的有效性。

英文摘要:

Black-box checking (BBC)} is a testing method for cyber-physical systems (CPSs) as well as software systems. BBC consists of active automata learning and model checking; a Mealy machine is learned from the system under test (SUT), and the learned Mealy machine is verified against a specification using model checking. When the Mealy machine violates the specification, the model checker returns an input witnessing the specification violation of the Mealy machine. We use it to refine the Mealy machine or conclude that the SUT violates the specification. Otherwise, we conduct equivalence testing to find an input witnessing the difference between the Mealy machine and the SUT. In the BBC for CPSs, equivalence testing tends to be time-consuming due to the time for the system execution. In this paper, we enhance the BBC utilizing model checking with strengthened specifications. By model checking with a strengthened specification, we have more chance to obtain an input witnessing the specification violation than model checking with the original specification. The refinement of the Mealy machine with such an input tends to reduce the number of equivalence testing, which improves the efficiency. We conducted experiments with an automotive benchmark. Our experiment results demonstrate the merit of our method.

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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