Fingerprinting Design Patterns. Guéhéneuc, Y., Sahraoui, H., & Zaidi, F. In Stroulia, E. & de Lucia, A., editors, Proceedings of the 11<sup>th</sup> Working Conference on Reverse Engineering (WCRE), pages 172–181, November, 2004. IEEE CS Press. 10 pages.
Fingerprinting Design Patterns [pdf]Paper  abstract   bibtex   
Design patterns describe \emphgood solutions to common and recurring problems in program design. The solutions are \emphdesign motifs which software engineers imitate and introduce in the architecture of their program. It is important to identify the design motifs used in a program architecture to understand solved design problems and to make informed changes to the program. The identification of \emphmicro-architectures similar to design motifs is difficult because of the large search space, \ie the many possible combinations of classes. We propose an experimental study of classes playing roles in design motifs using metrics and a machine learning algorithm to \emphfingerprint design motifs roles. Fingerprints are sets of metric values characterising classes playing a given role. We devise fingerprints experimentally using a repository of micro-architectures similar to design motifs. We show that fingerprints help in reducing the search space of micro-architectures similar to design motifs efficiently using the \ygg@patternComposite design motif and the \JHotDraw framework.
@INPROCEEDINGS{Gueheneuc04-WCRE-ClassFingerprinting,
  author = {Yann-Ga{\"e}l Gu{\'e}h{\'e}neuc and Houari Sahraoui and Farouk Zaidi},
  title = {Fingerprinting Design Patterns},
  booktitle = {Proceedings of the 11<sup>{th}</sup> Working Conference on Reverse Engineering ({WCRE})},
  year = {2004},
  month = {November},
  editor = {Eleni Stroulia and Andrea de Lucia},
  publisher = {IEEE CS Press},
  note = {10 pages.},
  abstract = {Design patterns describe \emph{good} solutions to common and recurring problems in program design. The solutions are \emph{design motifs} which software engineers imitate and introduce in the architecture of their program. It is important to identify the design motifs used in a program architecture to understand solved design problems and to make informed changes to the program. The identification of \emph{micro-architectures} similar to design motifs is difficult because of the large search space, \ie{} the many possible combinations of classes. We propose an experimental study of classes playing roles in design motifs using metrics and a machine learning algorithm to \emph{fingerprint} design motifs roles. Fingerprints are sets of metric values characterising classes playing a given role. We devise fingerprints experimentally using a repository of micro-architectures similar to design motifs. We show that fingerprints help in reducing the search space of micro-architectures similar to design motifs efficiently using the \ygg@pattern{Composite} design motif and the \JHotDraw{} framework.},
  grant = {NSERC DG},
  keywords = {Design patterns ; WCRE},
  kind = {MISA},
  language = {english},
  url = {http://www.ptidej.net/publications/documents/WCRE04.doc.pdf},
  pdf = {http://www.ptidej.net/publications/documents/WCRE04.ppt.pdf},
  pages = {172--181}
}
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