Fingerprinting Design Patterns

Fingerprinting Design Patterns. Gu�h�neuc, Y., Sahraoui, H., & Zaidi, F. In Stroulia, E. & de Lucia, A., editors, Proceedings of the 11th Working Conference on Reverse Engineering (WCRE), pages 172–181, November, 2004. IEEE CS Press. 10 pages.

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, ıe 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�l Gu�h�neuc and Houari Sahraoui and Farouk Zaidi},
   BOOKTITLE    = {Proceedings of the 11<sup>th</sup> Working Conference on Reverse Engineering (WCRE)},
   TITLE        = {Fingerprinting Design Patterns},
   YEAR         = {2004},
   OPTADDRESS   = {},
   OPTCROSSREF  = {},
   EDITOR       = {Eleni Stroulia and de Lucia, Andrea},
   MONTH        = {November},
   NOTE         = {10 pages.},
   OPTNUMBER    = {},
   OPTORGANIZATION = {},
   PAGES        = {172--181},
   PUBLISHER    = {IEEE CS Press},
   OPTSERIES    = {},
   OPTVOLUME    = {},
   KEYWORDS     = {Topic: <b>Design patterns</b>, Venue: <c>WCRE</c>},
   URL          = {http://www.ptidej.net/publications/documents/WCRE04.doc.pdf},
   PDF          = {http://www.ptidej.net/publications/documents/WCRE04.ppt.pdf},
   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.}
}

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