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ICSE 2020
Mon 5 - Sun 11 October 2020 Yongsan-gu, Seoul, South Korea
Wed 7 Oct 2020 16:30 - 16:45 at TBD2 - Prediction and Testing

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 7 Oct

16:00 - 17:00: Paper Presentations - Prediction and Testing at TBD2
icse-2020-Journal-First16:00 - 16:15
Paul TemplePReCISE, NaDi, UNamur, Mathieu Acher(Univ Rennes, Inria, IRISA), Jean-Marc JézéquelUniv Rennes - IRISA
icse-2020-Journal-First16:15 - 16:30
Yuanrui FanZhejiang University, Xin XiaMonash University, Daniel Alencar Da CostaUniversity of Otago, David LoSingapore Management University, Ahmed E. HassanQueen's University, Shanping LiZhejiang University
icse-2020-Journal-First16:30 - 16:45
Gemma CatolinoDelft University of Technology, Fabio Palomba University of Zurich, Francesca Arcelli FontanaUniversity of Milano-Bicocca, Andrea De LuciaUniversity of Salerno, Andy ZaidmanTU Delft, Filomena FerrucciUniversity of Salerno
icse-2020-Journal-First16:45 - 17:00
Chang-ai SunUniversity of Science and Technology Beijing, An FuUniversity of Science and Technology Beijing, Pak-Lok PoonSchool of Engineering & Technology, Central Queensland University, Australia, Xiaoyuan XieSchool of Computer Science, Wuhan University, China, Huai LiuSwinburne University of Technology, Tsong Yueh ChenSwinburne University of Technology