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On Implementation of the Assumption Generation Method for Component-Based Software Verification

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Advanced Topics in Intelligent Information and Database Systems (ACIIDS 2017)

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Abstract

The assume-guarantee verification has been recognized as a promising method for solving the state space explosion in modular model checking of component-based software. However, the counterexample analysis technique used in this method has huge complexity and the computational cost for generating assumptions is very high. As a result, the method is difficult to be applied in practice. Therefore, this paper presents two improvements of the assume-guarantee verification method in order to solve the above problems. The first one is a counterexample analysis method that is simple to implement but effective enough to prevent the verification process from infinite loops when considering the last action of counterexample as suffix in implementation. This is done by finding a suffix that can make the observation table not closed when being added to the suffix set of the table and use that suffix for the learning process. The second one is a reduction of the number of membership queries to be asked to teacher when learning assumptions. This results in a significantly faster speed in generating assumption than that of the original algorithm. An implemented tool and experimental results are also described to show the effectiveness of the improvements.

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Notes

  1. 1.

    http://www.coltech.vnu.edu.vn/~hungpn/IAGTool/.

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Acknowledgements

This work is supported by the project no. QG.16.31 granted by Vietnam National University, Hanoi (VNU).

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Correspondence to Pham Ngoc Hung .

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Le, CL., Tran, HV., Hung, P.N. (2017). On Implementation of the Assumption Generation Method for Component-Based Software Verification. In: Król, D., Nguyen, N., Shirai, K. (eds) Advanced Topics in Intelligent Information and Database Systems. ACIIDS 2017. Studies in Computational Intelligence, vol 710. Springer, Cham. https://doi.org/10.1007/978-3-319-56660-3_47

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  • DOI: https://doi.org/10.1007/978-3-319-56660-3_47

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