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Proof assisted bounded and unbounded symbolic model checking of software and system models

机译:证明辅助的软件和系统模型的有界和无界符号模型检查

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We have implemented various symbolic model checking algorithms, such as BMC, k-Induction and IC3 for B, Event-B and other modeling languages. The high-level nature of software models accounts for complicated constraints arising in these symbolic analysis techniques. In this article we suggest using static information stemming from proof obligations to simplify occurring constraints. We show how to include proof information in the aforementioned algorithms. Using different benchmarks we compare explicit state to symbolic model checking as well as techniques with and without proof assistance. In particular for models with large branching factor, e.g., due to complicated data values being manipulated, the symbolic techniques fare much better than explicit state model checking. The inclusion of proof information results in further performance improvements.
机译:我们已经实现了各种符号模型检查算法,例如BMC,k-Induction和针对B,事件B和其他建模语言的IC3。软件模型的高级性质解释了这些符号分析技术中出现的复杂约束。在本文中,我们建议使用源自证明义务的静态信息来简化发生的约束。我们展示了如何在上述算法中包括证明信息。使用不同的基准,我们将显式状态与符号模型检查以及有无辅助证据的技术进行比较。特别是对于具有较大分支因子的模型,例如,由于要处理复杂的数据值,符号技术的性能要比显式状态模型检查好得多。包含证明信息可进一步提高性能。

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