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Coverage Driven Test Generation and Consistency Algorithm

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Book cover Declarative Programming and Knowledge Management (INAP 2013, WLP 2013, WFLP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8439))

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Abstract

Coverage driven test generation (CDTG) is an essential part of functional verification where the objective is to generate input stimuli that maximize the functional coverage of a design. CDTG techniques analyze coverage results and adapt the stimulus generation process to improve the coverage. One of the important components of CDTG based tools is the constraint solver. The efficiency of the verification process depends on the performance of the solver. The speed of the solver can be increased if inconsistent values can be removed from the domain of input variables. In this paper, we propose a new efficient consistency algorithm called GACCC-op (generalized arc consistency on conjunction of constraints-optimized) which can be used along with the constraint solver of CDTG tools. The experimental results show that the proposed technique helps to reduce the time required for solution generation of CSPs by 19 %.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Concordia University, 1455 de Maisonneuve West, Montreal, QC, H3G 1M8, Canada

    Jomu George Mani Paret & Otmane Ait Mohamed

Authors
  1. Jomu George Mani Paret
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  2. Otmane Ait Mohamed
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Correspondence to Jomu George Mani Paret .

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Editors and Affiliations

  1. Universität Kiel, Kiel, Germany

    Michael Hanus

  2. CRACS & INESC-Porto LA, University of Porto, Porto, Portugal

    Ricardo Rocha

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Paret, J.G.M., Ait Mohamed, O. (2014). Coverage Driven Test Generation and Consistency Algorithm. In: Hanus, M., Rocha, R. (eds) Declarative Programming and Knowledge Management. INAP WLP WFLP 2013 2013 2013. Lecture Notes in Computer Science(), vol 8439. Springer, Cham. https://doi.org/10.1007/978-3-319-08909-6_9

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  • DOI: https://doi.org/10.1007/978-3-319-08909-6_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08908-9

  • Online ISBN: 978-3-319-08909-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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