• DocumentCode
    726476
  • Title

    Identifying Instances of Model Design Patterns and Antipatterns Using Model Clone Detection

  • Author

    Stephan, Matthew ; Cordy, James R.

  • Author_Institution
    Dept. of Comput. Sci. & Software Eng., Miami Univ., Oxford, OH, USA
  • fYear
    2015
  • fDate
    16-17 May 2015
  • Firstpage
    48
  • Lastpage
    53
  • Abstract
    A hurdle in the growth of model driven software engineering is our ability to evaluate the quality of models automatically. One perspective is that software quality is a function of the existence, or lack thereof, of good and bad properties, also known as patterns and antipatterns, respectively. In this paper, we introduce the notion of using model clone detection to detect model pattern and antipattern instances by looking for models that are cross clones of pattern models. By detecting patterns at the model level, analysis is accomplished earlier in the engineering process, can be applied to primarily model-based projects, and remains at the same level of abstraction that engineers are used to. We outline the process of using model clone detection for this purpose, including representing the patterns and detection of instances. We present some Simulink examples of pattern representations and discuss future work and research in the area.
  • Keywords
    software quality; Simulink; abstraction level; model clone detection; model design antipattern instance; model design pattern instance; model driven software engineering; model quality evaluation; pattern representation; software quality; Analytical models; Cloning; Computational modeling; Software engineering; Software packages; Unified modeling language; Design patterns; Model Clone Detection; Model Comparison; Model Quality; antipatterns;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modeling in Software Engineering (MiSE), 2015 IEEE/ACM 7th International Workshop on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/MiSE.2015.16
  • Filename
    7167402