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ICSE 2020
Wed 24 June - Thu 16 July 2020
Thu 9 Jul 2020 08:25 - 08:33 at Baekje - I16-Testing and Debugging 2 Chair(s): Rui Abreu

Defect models are analytical models for building empirical theories related to software quality. Prior studies often derive knowledge from such models using interpretation techniques, e.g., ANOVA Type-I. Recent work raises concerns that correlated metrics may impact the interpretation of defect models. Yet, the impact of correlated metrics in such models has not been investigated. In this paper, we investigate the impact of correlated metrics on the interpretation of defect models and the improvement of the interpretation of defect models when removing correlated metrics. Through a case study of 14 publicly- available defect datasets, we find that (1) correlated metrics have the largest impact on the consistency, the level of discrepancy, and the direction of the ranking of metrics, especially for ANOVA techniques. On the other hand, we find that removing all correlated metrics (2) improves the consistency of the produced rankings regardless of the ordering of metrics (except for ANOVA Type-I); (3) improves the consistency of ranking of metrics among the studied interpretation techniques; (4) impacts the model performance by less than 5 percentage points. Thus, when one wishes to derive sound interpretation from defect models, one must (1) mitigate correlated metrics especially for ANOVA analyses; and (2) avoid using ANOVA Type-I even if all correlated metrics are removed.

Thu 9 Jul

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08:05 - 09:05
I16-Testing and Debugging 2Technical Papers / Journal First at Baekje
Chair(s): Rui Abreu Instituto Superior T├ęcnico, U. Lisboa & INESC-ID
08:05
12m
Talk
Low-Overhead Deadlock PredictionTechnical
Technical Papers
Yan Cai Institute of Software, Chinese Academy of Sciences, Ruijie Meng University of Chinese Academy of Sciences, Jens Palsberg University of California, Los Angeles
08:17
8m
Talk
The Impact of Feature Reduction Techniques on Defect Prediction ModelsJ1
Journal First
Masanari Kondo Kyoto Institute of Technology, Cor-Paul Bezemer University of Alberta, Canada, Yasutaka Kamei Kyushu University, Ahmed E. Hassan Queen's University, Osamu Mizuno Kyoto Institute of Technology
08:25
8m
Talk
The Impact of Correlated Metrics on the Interpretation of Defect ModelsJ1
Journal First
Jirayus Jiarpakdee Monash University, Australia, Chakkrit Tantithamthavorn Monash University, Australia, Ahmed E. Hassan Queen's University
08:33
8m
Talk
The Impact of Mislabeled Changes by SZZ on Just-in-Time Defect PredictionJ1
Journal First
Yuanrui Fan Zhejiang University, Xin Xia Monash University, Daniel Alencar Da Costa University of Otago, David Lo Singapore Management University, Ahmed E. Hassan Queen's University, Shanping Li Zhejiang University
08:41
8m
Talk
Which Variables Should I Log?J1
Journal First
Zhongxin Liu Zhejiang University, Xin Xia Monash University, David Lo Singapore Management University, Zhenchang Xing Australia National University, Ahmed E. Hassan Queen's University, Shanping Li Zhejiang University
08:49
12m
Talk
Understanding the Automated Parameter Optimization on Transfer Learning for Cross-Project Defect Prediction: An Empirical StudyTechnicalArtifact Available
Technical Papers
Ke Li University of Exeter, Zilin Xiang University of Electronic Science and Technology of China, Tao Chen Loughborough University, Shuo Wang , Kay Chen Tan City University of Hong Kong
Pre-print