@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&ndash;181},
   PUBLISHER    = {IEEE CS Press},
   OPTSERIES    = {},
   OPTVOLUME    = {},
   KEYWORDS     = {Topic: <b>Design patterns</b>, 
      Rubrique : <b>patrons de conception</b>, Conference: WCRE},
   URL          = {http://www.ptidej.net/publications/documents/WCRE04.doc.pdf},
   PDF          = {http://www.ptidej.net/publications/documents/WCRE04.ppt.pdf},
   ABSTRACT     = {Design patterns describe good solutions to common and 
      recurring problems in program design. The solutions are 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 
      micro-architectures similar to design motifs is difficult because of 
      the large search space, i.e., 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 
      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 Composite design motif and the JHotDraw 
      framework.}
}

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The solutions are 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 micro-architectures similar to design motifs is difficult because of the large search space, i.e., 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 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 Composite design motif and the JHotDraw framework.","bibtex":"@INPROCEEDINGS{Gueheneuc04-WCRE-ClassFingerprinting,\r\n AUTHOR = {Yann-Ga�l Gu�h�neuc and Houari Sahraoui and Farouk Zaidi},\r\n BOOKTITLE = {Proceedings of the 11^th Working Conference on Reverse Engineering (WCRE)},\r\n TITLE = {Fingerprinting Design Patterns},\r\n YEAR = {2004},\r\n OPTADDRESS = {},\r\n OPTCROSSREF = {},\r\n EDITOR = {Eleni Stroulia and de Lucia, Andrea},\r\n MONTH = {November},\r\n NOTE = {10 pages.},\r\n OPTNUMBER = {},\r\n OPTORGANIZATION = {},\r\n PAGES = {172&ndash;181},\r\n PUBLISHER = {IEEE CS Press},\r\n OPTSERIES = {},\r\n OPTVOLUME = {},\r\n KEYWORDS = {Topic: <b>Design patterns</b>, \r\n Rubrique : <b>patrons de conception</b>, Conference: WCRE},\r\n URL = {http://www.ptidej.net/publications/documents/WCRE04.doc.pdf},\r\n PDF = {http://www.ptidej.net/publications/documents/WCRE04.ppt.pdf},\r\n ABSTRACT = {Design patterns describe good solutions to common and \r\n recurring problems in program design. The solutions are design motifs \r\n which software engineers imitate and introduce in the architecture of \r\n their program. It is important to identify the design motifs used in \r\n a program architecture to understand solved design problems and to \r\n make informed changes to the program. The identification of \r\n micro-architectures similar to design motifs is difficult because of \r\n the large search space, i.e., the many possible combinations of \r\n classes. We propose an experimental study of classes playing roles in \r\n design motifs using metrics and a machine learning algorithm to \r\n fingerprint design motifs roles. Fingerprints are sets of metric \r\n values characterising classes playing a given role. We devise \r\n fingerprints experimentally using a repository of micro-architectures \r\n similar to design motifs. We show that fingerprints help in reducing \r\n the search space of micro-architectures similar to design motifs \r\n efficiently using the Composite design motif and the JHotDraw \r\n framework.}\r\n}\r\n\r\n","author_short":["Gu�h�neuc, Y.","Sahraoui, H.","Zaidi, F."],"editor_short":["Stroulia, E.","de Lucia, A."],"key":"Gueheneuc04-WCRE-ClassFingerprinting","id":"Gueheneuc04-WCRE-ClassFingerprinting","bibbaseid":"guhneuc-sahraoui-zaidi-fingerprintingdesignpatterns-2004","role":"author","urls":{"Paper":"http://www.ptidej.net/publications/documents/WCRE04.doc.pdf"},"keyword":["Topic: <b>Design patterns</b>","Rubrique : <b>patrons de conception</b>","Conference: WCRE"],"metadata":{"authorlinks":{"gu�h�neuc, y":"https://bibbase.org/show?bib=http%3A%2F%2Fwww.yann-gael.gueheneuc.net%2FWork%2FPublications%2FBiblio%2Fcomplete-bibliography.bib&msg=embed","guéhéneuc, 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