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AnATLyzer: Static Analysis of ATL Model Transformations

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Composing Model-Based Analysis Tools

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Abstract

This chapter presents AnATLyzer—a tool for the static analysis of the ATL model transformation language. AnATLyzer is able to statically detect more than 50 types of problems in ATL transformation programs using different analysis techniques, some of them used in combination as per Challenge 2 (integrating and orchestrating analysis tools, cf. Chap. 5 of this book). The tool also provides a catalogue of more than 100 quick fixes (including quick fix recommendation via speculative analysis), visualisations and explanations to help understand the errors, and a synthesiser of witness models that permit reproducing the errors found. Altogether, this chapter focuses on how transformation developers can exploit AnATLyzer’s output results to understand and fix transformation problems and achieve higher quality transformations.

This case-study chapter illustrates concepts introduced in Chap. 7 and addresses Challenge 4 in Chap. 3 of this book.

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Author information

Authors and Affiliations

  1. Universidad de Murcia, Murcia, Spain

    Jesús Sánchez Cuadrado & Juan de Lara

  2. Autonomous University of Madrid, Madrid, Spain

    Esther Guerra

Authors
  1. Jesús Sánchez Cuadrado
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  2. Esther Guerra
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  3. Juan de Lara
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Corresponding author

Correspondence to Jesús Sánchez Cuadrado .

Editor information

Editors and Affiliations

  1. Karlsruhe Institute of Technology, Karlsruhe, Germany

    Robert Heinrich

  2. University of Málaga, Málaga, Spain

    Francisco Durán

  3. SRI International, Menlo Park, CA, USA

    Carolyn Talcott

  4. King's College London, London, UK

    Steffen Zschaler

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© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Cuadrado, J.S., Guerra, E., Lara, J.d. (2021). AnATLyzer: Static Analysis of ATL Model Transformations. In: Heinrich, R., Durán, F., Talcott, C., Zschaler, S. (eds) Composing Model-Based Analysis Tools. Springer, Cham. https://doi.org/10.1007/978-3-030-81915-6_12

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  • DOI: https://doi.org/10.1007/978-3-030-81915-6_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-81914-9

  • Online ISBN: 978-3-030-81915-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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