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An Evolutionary Approach to Translate Operational Specifications into Declarative Specifications

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Formal Methods: Foundations and Applications (SBMF 2016)

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Abstract

Various tools for program analysis, including run-time assertion checkers and static analyzers such as verification and test generation tools, require formal specifications of the programs being analyzed. Moreover, many of these tools and techniques require such specifications to be written in a particular style, or follow certain patterns, in order to obtain an acceptable performance from the corresponding analyses. Thus, having a formal specification sometimes is not enough for using a particular technique, since such specification may not be provided in the right formalism. In this paper, we deal with this problem in the increasingly common case of having an operational specification, while for analysis reasons requiring a declarative specification. We propose an evolutionary approach to translate an operational specification written in a sequential programming language, into a declarative specification, in relational logic. We perform experiments on a benchmark of data structure implementations, that show that translating representation invariants using our approach and verifying invariant preservation using the resulting specifications outperforms verification with specifications obtained using an existing semantics-preserving translation. Also, our evolutionary computation translation achieves very good precision in this context.

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Acknowledgements

The authors would like to thank the anonymous referees for their helpful comments. This work was partially supported by the Argentinian Agency for Scientific and Technological Promotion (ANPCyT), through grants PICT 2012 No. 1298, PICT 2013 No. 2624 and PICT 2013 No. 0080.

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Correspondence to Facundo Molina .

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Molina, F. et al. (2016). An Evolutionary Approach to Translate Operational Specifications into Declarative Specifications. In: Ribeiro, L., Lecomte, T. (eds) Formal Methods: Foundations and Applications. SBMF 2016. Lecture Notes in Computer Science(), vol 10090. Springer, Cham. https://doi.org/10.1007/978-3-319-49815-7_9

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  • DOI: https://doi.org/10.1007/978-3-319-49815-7_9

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