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A Framework for Evaluating Model-driven Architecture

Published: 30 December 2012
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Abstract

In the last few years, Model Driven Development (MDD) has become an interesting alternative for designing the self-adaptive software systems. In general, the ultimate goal of this technology is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of model-driven methodologies shows them all to include the principle of the separation of concerns as a key factor for obtaining high-quality and self-adaptable software systems. Each methodology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven architecture in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analyzing and evaluating the features of those development approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the proposed model-driven approaches in the related works, and emphasize on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modeling languages and modeling tools to the software developers.

Published in American Journal of Software Engineering and Applications (Volume 1, Issue 1)
DOI 10.11648/j.ajsea.20120101.12
Page(s) 10-22
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2012. Published by Science Publishing Group

Keywords

Model-Driven Architecture, Self-Adaptive Application, Context Oriented Software Development, Evaluation Framework Of Model-Driven Architecture

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  • APA Style

    Basel Magableh, Butheyna Rawashdeh, Stephen Barrett. (2012). A Framework for Evaluating Model-driven Architecture. American Journal of Software Engineering and Applications, 1(1), 10-22. https://doi.org/10.11648/j.ajsea.20120101.12

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    ACS Style

    Basel Magableh; Butheyna Rawashdeh; Stephen Barrett. A Framework for Evaluating Model-driven Architecture. Am. J. Softw. Eng. Appl. 2012, 1(1), 10-22. doi: 10.11648/j.ajsea.20120101.12

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    AMA Style

    Basel Magableh, Butheyna Rawashdeh, Stephen Barrett. A Framework for Evaluating Model-driven Architecture. Am J Softw Eng Appl. 2012;1(1):10-22. doi: 10.11648/j.ajsea.20120101.12

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  • @article{10.11648/j.ajsea.20120101.12,
      author = {Basel Magableh and Butheyna Rawashdeh and Stephen Barrett},
      title = {A Framework for Evaluating Model-driven Architecture},
      journal = {American Journal of Software Engineering and Applications},
      volume = {1},
      number = {1},
      pages = {10-22},
      doi = {10.11648/j.ajsea.20120101.12},
      url = {https://doi.org/10.11648/j.ajsea.20120101.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.20120101.12},
      abstract = {In the last few years, Model Driven Development (MDD) has become an interesting alternative for designing the self-adaptive software systems. In general, the ultimate goal of this technology is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of model-driven methodologies shows them all to include the principle of the separation of concerns as a key factor for obtaining high-quality and self-adaptable software systems. Each methodology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven architecture in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analyzing and evaluating the features of those development approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the proposed model-driven approaches in the related works, and emphasize on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modeling languages and modeling tools to the software developers.},
     year = {2012}
    }
    

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    T1  - A Framework for Evaluating Model-driven Architecture
    AU  - Basel Magableh
    AU  - Butheyna Rawashdeh
    AU  - Stephen Barrett
    Y1  - 2012/12/30
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    N1  - https://doi.org/10.11648/j.ajsea.20120101.12
    DO  - 10.11648/j.ajsea.20120101.12
    T2  - American Journal of Software Engineering and Applications
    JF  - American Journal of Software Engineering and Applications
    JO  - American Journal of Software Engineering and Applications
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    PB  - Science Publishing Group
    SN  - 2327-249X
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    AB  - In the last few years, Model Driven Development (MDD) has become an interesting alternative for designing the self-adaptive software systems. In general, the ultimate goal of this technology is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of model-driven methodologies shows them all to include the principle of the separation of concerns as a key factor for obtaining high-quality and self-adaptable software systems. Each methodology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven architecture in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analyzing and evaluating the features of those development approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the proposed model-driven approaches in the related works, and emphasize on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modeling languages and modeling tools to the software developers.
    VL  - 1
    IS  - 1
    ER  - 

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Author Information
  • School of Computer Science and Informatics,University College Dublin,Ireland

  • Faculty of Computer Science and Information, Ajloun University College, AL-Balqa Applied University, Ajloun, Jordan

  • School of Computer Science and Statistics, Trinity College, University of Dublin, Ireland

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