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Accelerating Predicate Abstraction by Minimum Unsatisfiable Cores Extraction

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Book cover Theoretical Computer Science (NCTCS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1352))

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Abstract

With the growing scale and complexity of software and hardware designs, model checking generally results in the combination explosion of state space. Predicate abstraction is an important technique to solve this problem. The number of refinement iterations will be reduced by extracting the unsatisfiable cores. The smaller unsatisfiable cores are, the more false counterexamples are eliminated. Therefore, a fast algorithm of deriving the minimum unsatisfiable cores is employed in the formal verification tool of hardware. The two optimal algorithms of computing minimum unsatisfiable cores are compared on the instruction Cache unit of a microprocessor. The experimental results showed that the greedy-generic algorithm outperforms the branch-bound algorithm. Furthermore we analyzed that the unsatisfiable cores plays an important role in predicate abstraction, and it can improve the efficiency of model checking.

Supported by the National Natural Science Foundation of China under grant No. 62072464 and U19A2062, and the National Laboratory of Parallel and Distributed Processing Open Fund under grant No. WDZC20205500116.

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Authors and Affiliations

  1. School of Computer, National University of Defense Technology, Changsha, 410073, China

    Jianmin Zhang, Tiejun Li & Kefan Ma

Authors
  1. Jianmin Zhang
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  2. Tiejun Li
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  3. Kefan Ma
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Corresponding author

Correspondence to Jianmin Zhang .

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Editors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    Kun He

  2. Guangxi University, Nanning, China

    Cheng Zhong

  3. National University of Defense Technology, Changsha, China

    Zhiping Cai

  4. Nanjing University, Nanjing, China

    Yitong Yin

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Zhang, J., Li, T., Ma, K. (2021). Accelerating Predicate Abstraction by Minimum Unsatisfiable Cores Extraction. In: He, K., Zhong, C., Cai, Z., Yin, Y. (eds) Theoretical Computer Science. NCTCS 2020. Communications in Computer and Information Science, vol 1352. Springer, Singapore. https://doi.org/10.1007/978-981-16-1877-2_1

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  • DOI: https://doi.org/10.1007/978-981-16-1877-2_1

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-1876-5

  • Online ISBN: 978-981-16-1877-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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