@INPROCEEDINGS{Petrillo17-QRS-BreakpointToggling,
   AUTHOR       = {Fabio Petrillo and Hyan Mandian and Aiko Yamashita and 
      Foutse Khomh and Yann-Ga�l Gu�h�neuc},
   BOOKTITLE    = {Proceedings of the 3<sup>rd</sup> International Conference on Software Quality, Reliability, and Security (QRS)},
   TITLE        = {How Do Developers Toggle Breakpoints? Observational 
      Studies},
   YEAR         = {2017},
   OPTADDRESS   = {},
   OPTCROSSREF  = {},
   EDITOR       = {Manuel Nu�ez and Tadashi Dohi and Xiaoying Bai},
   MONTH        = {July},
   NOTE         = {10 pages.},
   OPTNUMBER    = {},
   OPTORGANIZATION = {},
   PAGES        = {285--295},
   PUBLISHER    = {IEEE CS Press},
   OPTSERIES    = {},
   OPTVOLUME    = {},
   KEYWORDS     = {Topic: <b>Program comprehension</b>, Venue: <c>QRS</c>},
   URL          = {http://www.ptidej.net/publications/documents/QRS17a.doc.pdf},
   PDF          = {http://www.ptidej.net/publications/documents/QRS17a.ppt.pdf},
   ABSTRACT     = {In software engineering, a smell is a part of a software 
      system's source code with a poor quality and that may indicate a 
      deeper problem. Although many kinds of smells have been studied to 
      analyze their causes, their behavior, and their impact on software 
      quality, those smells typically are studied independently from each 
      other. However, if two smells coincide inside a class, this could 
      increases their negative effect (e.g., spaghetti code that is being 
      cloned across the system). In this paper we report results from an 
      empirical study conducted to examine the relationship between two 
      specific kinds of smells: code clones and antipatterns. We conducted 
      our study on three open-source software systems: Azureus, Eclipse, 
      and JHotDraw. Results show that between 32\% and 63\% of classes in 
      the analysed systems present co-occurrence of smells, and that such 
      classes are more risky in term of fault-proneness.}
}

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Observational Studies","author_short":["Petrillo, F.","Mandian, H.","Yamashita, A.","Khomh, F.","Gu�h�neuc, Y."],"year":2017,"bibtype":"inproceedings","biburl":"http://www.yann-gael.gueheneuc.net/Work/Publications/Biblio/complete-bibliography.bib","bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["Fabio"],"propositions":[],"lastnames":["Petrillo"],"suffixes":[]},{"firstnames":["Hyan"],"propositions":[],"lastnames":["Mandian"],"suffixes":[]},{"firstnames":["Aiko"],"propositions":[],"lastnames":["Yamashita"],"suffixes":[]},{"firstnames":["Foutse"],"propositions":[],"lastnames":["Khomh"],"suffixes":[]},{"firstnames":["Yann-Ga�l"],"propositions":[],"lastnames":["Gu�h�neuc"],"suffixes":[]}],"booktitle":"Proceedings of the 3^rd International Conference on Software Quality, Reliability, and Security (QRS)","title":"How Do Developers Toggle Breakpoints? Observational Studies","year":"2017","optaddress":"","optcrossref":"","editor":[{"firstnames":["Manuel"],"propositions":[],"lastnames":["Nu�ez"],"suffixes":[]},{"firstnames":["Tadashi"],"propositions":[],"lastnames":["Dohi"],"suffixes":[]},{"firstnames":["Xiaoying"],"propositions":[],"lastnames":["Bai"],"suffixes":[]}],"month":"July","note":"10 pages.","optnumber":"","optorganization":"","pages":"285–295","publisher":"IEEE CS Press","optseries":"","optvolume":"","keywords":"Topic: <b>Program comprehension</b>, Venue: <c>QRS</c>","url":"http://www.ptidej.net/publications/documents/QRS17a.doc.pdf","pdf":"http://www.ptidej.net/publications/documents/QRS17a.ppt.pdf","abstract":"In software engineering, a smell is a part of a software system's source code with a poor quality and that may indicate a deeper problem. Although many kinds of smells have been studied to analyze their causes, their behavior, and their impact on software quality, those smells typically are studied independently from each other. However, if two smells coincide inside a class, this could increases their negative effect (e.g., spaghetti code that is being cloned across the system). In this paper we report results from an empirical study conducted to examine the relationship between two specific kinds of smells: code clones and antipatterns. We conducted our study on three open-source software systems: Azureus, Eclipse, and JHotDraw. Results show that between 32% and 63% of classes in the analysed systems present co-occurrence of smells, and that such classes are more risky in term of fault-proneness.","bibtex":"@INPROCEEDINGS{Petrillo17-QRS-BreakpointToggling,\r\n AUTHOR = {Fabio Petrillo and Hyan Mandian and Aiko Yamashita and \r\n Foutse Khomh and Yann-Ga�l Gu�h�neuc},\r\n BOOKTITLE = {Proceedings of the 3^rd International Conference on Software Quality, Reliability, and Security (QRS)},\r\n TITLE = {How Do Developers Toggle Breakpoints? Observational \r\n Studies},\r\n YEAR = {2017},\r\n OPTADDRESS = {},\r\n OPTCROSSREF = {},\r\n EDITOR = {Manuel Nu�ez and Tadashi Dohi and Xiaoying Bai},\r\n MONTH = {July},\r\n NOTE = {10 pages.},\r\n OPTNUMBER = {},\r\n OPTORGANIZATION = {},\r\n PAGES = {285--295},\r\n PUBLISHER = {IEEE CS Press},\r\n OPTSERIES = {},\r\n OPTVOLUME = {},\r\n KEYWORDS = {Topic: <b>Program comprehension</b>, Venue: <c>QRS</c>},\r\n URL = {http://www.ptidej.net/publications/documents/QRS17a.doc.pdf},\r\n PDF = {http://www.ptidej.net/publications/documents/QRS17a.ppt.pdf},\r\n ABSTRACT = {In software engineering, a smell is a part of a software \r\n system's source code with a poor quality and that may indicate a \r\n deeper problem. Although many kinds of smells have been studied to \r\n analyze their causes, their behavior, and their impact on software \r\n quality, those smells typically are studied independently from each \r\n other. However, if two smells coincide inside a class, this could \r\n increases their negative effect (e.g., spaghetti code that is being \r\n cloned across the system). In this paper we report results from an \r\n empirical study conducted to examine the relationship between two \r\n specific kinds of smells: code clones and antipatterns. We conducted \r\n our study on three open-source software systems: Azureus, Eclipse, \r\n and JHotDraw. Results show that between 32\\% and 63\\% of classes in \r\n the analysed systems present co-occurrence of smells, and that such \r\n classes are more risky in term of fault-proneness.}\r\n}\r\n\r\n","author_short":["Petrillo, F.","Mandian, H.","Yamashita, A.","Khomh, F.","Gu�h�neuc, Y."],"editor_short":["Nu�ez, M.","Dohi, T.","Bai, X."],"key":"Petrillo17-QRS-BreakpointToggling","id":"Petrillo17-QRS-BreakpointToggling","bibbaseid":"petrillo-mandian-yamashita-khomh-guhneuc-howdodeveloperstogglebreakpointsobservationalstudies-2017","role":"author","urls":{"Paper":"http://www.ptidej.net/publications/documents/QRS17a.doc.pdf"},"keyword":["Topic: <b>Program comprehension</b>","Venue: <c>QRS</c>"],"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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