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ICSE 2020
Wed 24 June - Thu 16 July 2020
Wed 8 Jul 2020 16:46 - 16:54 at Silla - A12-Testing Chair(s): Sasa Misailovic

Code smells are sub-optimal implementation choices applied by developers that have the effect of negatively impacting, among others, the change-proneness of the affected classes. Based on this consideration, in this paper we conjecture that code smell-related information can be effectively exploited to improve the performance of change prediction models, i.e., models having the goal of indicating which classes are more likely to change in the future. We exploit the so-called intensity index—a previously defined metric that captures the severity of a code smell—and evaluate its contribution when added as additional feature in the context of three state of the art change prediction models based on product, process, and developer-based features. We also compare the performance achieved by the proposed model with a model based on previously defined antipattern metrics, a set of indicators computed considering the history of code smells in files. Our results report that (i) the prediction performance of the intensity-including models is statistically better than the baselines and, (ii) the intensity is a better predictor than antipattern metrics. We observed some orthogonality between the set of change-prone and non-change-prone classes correctly classified by the models relying on intensity and antipattern metrics: for this reason, we also devise and evaluate a smell-aware combined change prediction model including product, process, developer-based, and smell-related features. We show that the F-Measure of this model is notably higher than other models.

Wed 8 Jul
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16:05 - 17:05: Paper Presentations - A12-Testing at Silla
Chair(s): Sasa MisailovicUniversity of Illinois at Urbana-Champaign
icse-2020-papers16:05 - 16:17
Thodoris SotiropoulosAthens University of Economics and Business, Dimitris MitropoulosAthens University of Economics and Business, Diomidis SpinellisAthens University of Economics and Business
icse-2020-Journal-First16:17 - 16:25
Paul TemplePReCISE, NaDi, UNamur, Mathieu Acher(Univ Rennes, Inria, IRISA), Jean-Marc JézéquelUniv Rennes - IRISA
Demonstrations16:25 - 16:28
Matias MartinezUniversité Polytechnique Hauts-de-France, Anne EtienUniversité de Lille, CNRS, Inria, Centrale Lille, UMR 9189 –CRIStAL, Stéphane Ducasse INRIA Lille, Christopher FuhrmanÉcole de technologie supérieure
Pre-print Media Attached
icse-2020-New-Ideas-and-Emerging-Results16:28 - 16:34
Valerio TerragniUniversità della Svizzera Italiana, Pasquale SalzaUniversity of Zurich, Filomena FerrucciUniversity of Salerno
Pre-print Media Attached
icse-2020-papers16:34 - 16:46
Jordan HenkelUniversity of Wisconsin–Madison, Christian BirdMicrosoft Research, Shuvendu K. LahiriMicrosoft Research, Thomas RepsUniversity of Wisconsin-Madison, USA
icse-2020-Journal-First16:46 - 16:54
Gemma CatolinoDelft University of Technology, Fabio PalombaUniversity of Salerno, Francesca Arcelli FontanaUniversity of Milano-Bicocca, Andrea De LuciaUniversity of Salerno, Andy ZaidmanTU Delft, Filomena FerrucciUniversity of Salerno
DOI Pre-print
Demonstrations16:54 - 16:57
Phu X. MaiUniversity of Luxembourg, Arda GoknilSnT, University of Luxembourg, Fabrizio PastoreUniversity of Luxembourg, Lionel C. BriandSnT Centre/University of Luxembourg