@ARTICLE{Kpodjedo13-JSME-ETGMEvolution,
   AUTHOR       = {S�gla Kpodjedo and Filippo Ricca and Philippe Galinier and 
      Giuliano Antoniol and Yann-Ga�l Gu�h�neuc},
   JOURNAL      = {Journal of Software Maintenance and Evolution: Research and Practice (JSME)},
   TITLE        = {Studying Software Evolution of Large Object-oriented 
      Software Systems using an ETGM Algorithm},
   YEAR         = {2013},
   MONTH        = {September},
   NOTE         = {28 pages.},
   NUMBER       = {2},
   PAGES        = {139--163},
   VOLUME       = {25},
   EDITOR       = {Gerardo Canfora and David Raffo and Darren Dalcher},
   KEYWORDS     = {Topic: <b>Evolution patterns</b>, Venue: <b>JSME</b>, 
      Venue: <b>JSEP</b>},
   PUBLISHER    = {Wiley},
   URL          = {http://www.ptidej.net/publications/documents/JSME10.doc.pdf},
   ABSTRACT     = {Analyzing and understanding the evolution of large 
      object-oriented software systems is an important but difficult task, 
      in which matching algorithms play a fundamental role. An 
      error-tolerant graph matching (ETGM) algorithm is able to identify 
      evolving classes that maintain a stable structure of relations 
      (associations, inheritances, and aggregations) with other classes and 
      that, thus, likely constitute the backbone of the system. Therefore, 
      we first develop a novel ETGM algorithm to study the evolution of 
      class diagrams. This algorithm improves the performance of our 
      previous algorithm. Second, we describe the process of building an 
      oracle to test and study our algorithm. Third, we report for the new 
      algorithm the impact of the algorithm parameters on the F-measure 
      summarizing precision and recall. Finally, with tuned algorithm 
      parameters, we carry out and report an extensive empirical evaluation 
      of our algorithm. Overall we show that: this novel algorithm is 
      scalable, stable and has better time performance. In our empirical 
      evaluation, we use small, \ie{} Rhino, medium, \ie{} Azureus and 
      ArgoUML, and large systems, \ie{} Mozilla and Eclipse.}
}

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An error-tolerant graph matching (ETGM) algorithm is able to identify evolving classes that maintain a stable structure of relations (associations, inheritances, and aggregations) with other classes and that, thus, likely constitute the backbone of the system. Therefore, we first develop a novel ETGM algorithm to study the evolution of class diagrams. This algorithm improves the performance of our previous algorithm. Second, we describe the process of building an oracle to test and study our algorithm. Third, we report for the new algorithm the impact of the algorithm parameters on the F-measure summarizing precision and recall. Finally, with tuned algorithm parameters, we carry out and report an extensive empirical evaluation of our algorithm. Overall we show that: this novel algorithm is scalable, stable and has better time performance. In our empirical evaluation, we use small, ıe Rhino, medium, ıe Azureus and ArgoUML, and large systems, ıe Mozilla and Eclipse.","bibtex":"@ARTICLE{Kpodjedo13-JSME-ETGMEvolution,\r\n AUTHOR = {S�gla Kpodjedo and Filippo Ricca and Philippe Galinier and \r\n Giuliano Antoniol and Yann-Ga�l Gu�h�neuc},\r\n JOURNAL = {Journal of Software Maintenance and Evolution: Research and Practice (JSME)},\r\n TITLE = {Studying Software Evolution of Large Object-oriented \r\n Software Systems using an ETGM Algorithm},\r\n YEAR = {2013},\r\n MONTH = {September},\r\n NOTE = {28 pages.},\r\n NUMBER = {2},\r\n PAGES = {139--163},\r\n VOLUME = {25},\r\n EDITOR = {Gerardo Canfora and David Raffo and Darren Dalcher},\r\n KEYWORDS = {Topic: <b>Evolution patterns</b>, Venue: <b>JSME</b>, \r\n Venue: <b>JSEP</b>},\r\n PUBLISHER = {Wiley},\r\n URL = {http://www.ptidej.net/publications/documents/JSME10.doc.pdf},\r\n ABSTRACT = {Analyzing and understanding the evolution of large \r\n object-oriented software systems is an important but difficult task, \r\n in which matching algorithms play a fundamental role. An \r\n error-tolerant graph matching (ETGM) algorithm is able to identify \r\n evolving classes that maintain a stable structure of relations \r\n (associations, inheritances, and aggregations) with other classes and \r\n that, thus, likely constitute the backbone of the system. Therefore, \r\n we first develop a novel ETGM algorithm to study the evolution of \r\n class diagrams. This algorithm improves the performance of our \r\n previous algorithm. Second, we describe the process of building an \r\n oracle to test and study our algorithm. Third, we report for the new \r\n algorithm the impact of the algorithm parameters on the F-measure \r\n summarizing precision and recall. Finally, with tuned algorithm \r\n parameters, we carry out and report an extensive empirical evaluation \r\n of our algorithm. Overall we show that: this novel algorithm is \r\n scalable, stable and has better time performance. 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