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A Model Repository Description Language - MRDL

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Software Reuse: Bridging with Social-Awareness (ICSR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9679))

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Abstract

Repository-based development of software systems has gained more attention recently by addressing new challenges such as security and dependability. However, there are still gaps in existing modeling languages and/or formalisms dedicated to define model repositories and the way how to reuse them in the automation of software development. Thus, there is a strong requirement for defining a model repository description language not only as a modeling approach, but also as a suitable instrument to support system and software engineers in the activity of search and retrieval of appropriate models beyond keyword-based search. Moreover, modeling approaches allow using tools for the specification and the exploitation of the designed artifacts (e.g. analysis and evaluation). The goal of this paper is to advance the state of the art in model repository description for software and systems engineering. In particular, we have designed a flexible and extensible modeling language, by means of an OMG style metamodel, to specify model repositories for modeling artifacts, and we have defined an operational architecture for development tools. In particular, we show the feasibility of our own approach by reporting some preliminary prototype providing a model-based repository of security and dependability (S&D) pattern models.

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Notes

  1. 1.

    Ecore is a meta-metamodel.

  2. 2.

    https://eclipse.org/modeling/emft/.

  3. 3.

    http://www.omg.org/spec/QVT/.

  4. 4.

    http://www.eclipse.org/cdo/.

  5. 5.

    http://www.semcomdt.org/.

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Correspondence to Brahim Hamid .

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Hamid, B. (2016). A Model Repository Description Language - MRDL. In: Kapitsaki, G., Santana de Almeida, E. (eds) Software Reuse: Bridging with Social-Awareness. ICSR 2016. Lecture Notes in Computer Science(), vol 9679. Springer, Cham. https://doi.org/10.1007/978-3-319-35122-3_23

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  • DOI: https://doi.org/10.1007/978-3-319-35122-3_23

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