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Systematic Testing of Graph Transformations: A Practical Approach Based on Graph Patterns

  • Conference paper
Theory and Practice of Model Transformations (ICMT 2013)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7909))

Abstract

Correctness is an essential property of model transformations. Although testing is a well-accepted method for assuring software quality in general, the properties of declarative transformation languages often prevent a direct application of testing strategies from imperative programming languages. A key challenge of transformation testing concerns limiting the testing effort by a good stop criterion. In this work, we tackle this issue for programmed graph transformations, and present a practical methodology to derive sufficient test suites based on a new coverage notion inspired by mutation analysis. We systematically generate requirement (graph) patterns from the transformation under test, applying different requirement construction strategies, and analyze the approach in terms of practicability, test suite quality and the ability to guide and support test case construction.

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Author information

Authors and Affiliations

  1. Real-Time Systems Lab, Technische Universität Darmstadt, Merckstraße 25, 64283, Darmstadt, Germany

    Martin Wieber & Andy Schürr

Authors
  1. Martin Wieber
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  2. Andy Schürr
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Editor information

Editors and Affiliations

  1. Queensland University of Technology, 4000, Brisbane, QLD, Australia

    Keith Duddy

  2. Vienna University of Technology, 1040, Vienna, Austria

    Gerti Kappel

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Wieber, M., Schürr, A. (2013). Systematic Testing of Graph Transformations: A Practical Approach Based on Graph Patterns. In: Duddy, K., Kappel, G. (eds) Theory and Practice of Model Transformations. ICMT 2013. Lecture Notes in Computer Science, vol 7909. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38883-5_18

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  • DOI: https://doi.org/10.1007/978-3-642-38883-5_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38882-8

  • Online ISBN: 978-3-642-38883-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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