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Interpretation of Linguistic Architecture

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Modelling Foundations and Applications (ECMFA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8569))

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Abstract

The megamodeling language MegaL is designed to model the linguistic architecture of software systems: the relationships between software artifacts (e.g., files), software languages (e.g., programming languages), and software technologies (e.g., code generators) used in a system. The present paper delivers a form of interpretation for such megamodels: resolution of megamodel elements to resources (e.g., system artifacts) and evaluation of relationships, subject to designated programs (such as pluggable ‘tools’ for checking). Interpretation reduces concerns about the adequacy and meaning of megamodels, as it helps to apply the megamodels to actual systems. We leverage Linked Data principles for surfacing resolved megamodels by linking, for example, artifacts to GitHub repositories or concepts to DBpedia resources. We provide an executable specification (i.e., semantics) of interpreted megamodels and we discuss an implementation in terms of an object-oriented framework with dynamically loaded plugins.

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Author information

Authors and Affiliations

  1. Software Languages Team, University of Koblenz-Landau, Germany

    Ralf Lämmel & Andrei Varanovich

Authors
  1. Ralf Lämmel
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  2. Andrei Varanovich
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Editor information

Editors and Affiliations

  1. Computer Science Department, AtlanMod team (Inria, Mines Nantes, LINA), École des Mines de Nantes, 4, rue Alfred Kastler, 44307, Nantes Cedex 3, France

    Jordi Cabot

  2. IBM Research, Haifa University Campus, Mount Carmel, 31905, Haifa, Israel

    Julia Rubin

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© 2014 Springer International Publishing Switzerland

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Lämmel, R., Varanovich, A. (2014). Interpretation of Linguistic Architecture. In: Cabot, J., Rubin, J. (eds) Modelling Foundations and Applications. ECMFA 2014. Lecture Notes in Computer Science, vol 8569. Springer, Cham. https://doi.org/10.1007/978-3-319-09195-2_5

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  • DOI: https://doi.org/10.1007/978-3-319-09195-2_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09194-5

  • Online ISBN: 978-3-319-09195-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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