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GECO: A Generator Composition Approach for Aspect-Oriented DSLs

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Theory and Practice of Model Transformations (ICMT 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9765))

Abstract

Code and model generators that are employed in model-driven engineering usually face challenges caused by complexity and tight coupling of generator implementations, particularly when multiple metamodels are involved. As a consequence maintenance, evolution and reuse of generators is expensive and error-prone.

We address these challenges with a two fold approach for generator composition, called GECO, which subdivides generators in fragments and modules. (1) fragments are combined utilizing megamodel patterns. These patterns are based on the relationship between base and aspect metamodel, and define that each fragment relates only to one source and target metamodel. (2) fragments are modularized along transformation aspects, such as model navigation, and metamodel semantics.

We evaluate our approach with two case studies from different domains. The obtained generators are assessed with modularity and complexity metrics, covering architecture and method level. Our results show that the generator modularity is preserved during evolution utilizing GECO.

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Acknowledgement

This work was supported by the DFG (German Research Foundation) under the priority program SPP 1593: Design For Future – Managed Software Evolution (grants HA 2038/4-1, RE 1674/7-1) and the Helmholtz Association of German Research Centers.

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Authors and Affiliations

  1. Kiel University, Christian-Albrechts-Platz 4, Kiel, Germany

    Reiner Jung & Wilhelm Hasselbring

  2. Karlsruhe Institute of Technology, Am Fasanengarten 5, Karlsruhe, Germany

    Robert Heinrich

Authors
  1. Reiner Jung
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  2. Robert Heinrich
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  3. Wilhelm Hasselbring
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Corresponding author

Correspondence to Reiner Jung .

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Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    Pieter Van Gorp

  2. University of Paderborn, Paderborn, Germany

    Gregor Engels

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Jung, R., Heinrich, R., Hasselbring, W. (2016). GECO: A Generator Composition Approach for Aspect-Oriented DSLs. In: Van Gorp, P., Engels, G. (eds) Theory and Practice of Model Transformations. ICMT 2016. Lecture Notes in Computer Science(), vol 9765. Springer, Cham. https://doi.org/10.1007/978-3-319-42064-6_10

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  • DOI: https://doi.org/10.1007/978-3-319-42064-6_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42063-9

  • Online ISBN: 978-3-319-42064-6

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