@INPROCEEDINGS{Antoniol08-CASCON-ClassificationofChangeReq,
   AUTHOR       = {Giuliano Antoniol and Kamel Ayari and 
      Di Penta, Massimiliano and Foutse Khomh and Yann-Ga�l Gu�h�neuc},
   BOOKTITLE    = {Proceedings of the 18<sup>th</sup> IBM Centers for Advanced Studies Conference (CASCON)},
   TITLE        = {Is It a Bug or an Enhancement? A Text-based Approach to 
      Classify Change Requests},
   YEAR         = {2008},
   OPTADDRESS   = {},
   OPTCROSSREF  = {},
   EDITOR       = {Mark Vigder and Marsha Chechik},
   MONTH        = {October},
   NOTE         = {Most Influential Paper Award at CASCON'18. 15 pages.},
   OPTNUMBER    = {},
   OPTORGANIZATION = {},
   PAGES        = {23--37},
   PUBLISHER    = {ACM Press},
   OPTSERIES    = {},
   OPTVOLUME    = {},
   KEYWORDS     = {Topic: <b>Evolution patterns</b>, Venue: <i>CASCON</i>},
   URL          = {http://www.ptidej.net/publications/documents/CASCON08.doc.pdf},
   PDF          = {http://www.ptidej.net/publications/documents/CASCON08.ppt.pdf},
   ABSTRACT     = {Bug tracking systems are valuable assets for managing 
      maintenance activities. They are widely used in open-source projects 
      as well as in the software industry. They collect many different 
      kinds of issues: requests for defect fixing, enhancements, 
      refactoring/restructuring activities and organizational issues. These 
      different kinds of issues are simply labeled as ``bug" for lack of a 
      better classification support or of knowledge about the possible 
      kinds. This paper investigates whether the text of the issues posted 
      in bug tracking systems is enough to classify them into corrective 
      maintenance and other kinds of activities. We show that alternating 
      decision trees, naive Bayes classifiers, and logistic regression can 
      be used to accurately distinguish bugs from other kinds of issues. 
      Results from empirical studies performed on issues for Mozilla, 
      Eclipse, and JBoss indicate that issues can be classified with 
      between 77\% and 82\% of correct decisions.}
}

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These \r\n different kinds of issues are simply labeled as ``bug\" for lack of a \r\n better classification support or of knowledge about the possible \r\n kinds. This paper investigates whether the text of the issues posted \r\n in bug tracking systems is enough to classify them into corrective \r\n maintenance and other kinds of activities. 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