Blogs (1) >>
ICSE 2019
Sat 25 - Fri 31 May 2019 Montreal, QC, Canada
Fri 31 May 2019 11:50 - 12:00 at Laurier - Defect Prediction Chair(s): Burak Turhan

Defect models that are trained on class imbalanced datasets (i.e., the proportion of defective and clean modules is not equally represented) are highly susceptible to produce inaccurate prediction models. Prior research compares the impact of class rebalancing techniques on the performance of defect models but arrives at contradictory conclusions due to the use of different choice of datasets, classification techniques, and performance measures. Such contradictory conclusions make it hard to derive practical guidelines for whether class rebalancing techniques should be applied in the context of defect models. In this paper, we investigate the impact of class rebalancing techniques on performance measures and the interpretation of defect models. We also investigate the experimental settings in which class rebalancing techniques are beneficial for defect models. Through a case study of 101 datasets that span across proprietary and open-source systems, we conclude that the impact of class rebalancing techniques on the performance of defect prediction models depends on the used performance measure and the used classification techniques. We observe that the optimized SMOTE technique and the under-sampling technique are beneficial when quality assurance teams wish to increase AUC and Recall, respectively, but they should be avoided when deriving knowledge and understandings from defect models.

Fri 31 May
Times are displayed in time zone: Eastern Time (US & Canada) change

11:00 - 12:30
11:00
10m
Talk
Perceptions, Expectations, and Challenges in Defect PredictionJournal-First
Journal-First Papers
Zhiyuan WanZhejiang University, Xin XiaMonash University, Ahmed E. HassanQueen's University, David LoSingapore Management University, Jianwei Yin, Xiaohu Yang
11:10
20m
Talk
Mining Software Defects: Should We Consider Affected Releases?Artifacts AvailableArtifacts Evaluated ReusableTechnical Track
Technical Track
Suraj YatishThe University of Adelaide, Jirayus JiarpakdeeMonash University, Patanamon ThongtanunamThe University of Melbourne, Chakkrit TantithamthavornMonash University, Australia
11:30
20m
Talk
Class Imbalance Evolution and Verification Latency in Just-in-Time Software Defect PredictionTechnical Track
Technical Track
George CabralUniversity of Birmingham, Leandro Minku , Emad ShihabConcordia University, Suhaib MujahidConcordia University
11:50
10m
Talk
The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction ModelsJournal-First
Journal-First Papers
Chakkrit TantithamthavornMonash University, Australia, Ahmed E. HassanQueen's University, Kenichi MatsumotoNara Institute of Science and Technology
Pre-print
12:00
10m
Talk
On the Relative Value of Data Resampling Approaches for Software Defect PredictionJournal-First
Journal-First Papers
Kwabena E. BenninBlekinge Institute of Technology, SERL Sweden, Jacky Keung, Akito Monden
Authorizer link
12:10
10m
Talk
Energy-Based Anomaly Detection A New Perspective for Predicting Software FailuresNIER Distinguished Paper AwardNIER
New Ideas and Emerging Results
Cristina MonniUniversità della Svizzera Italiana, Mauro PezzeUniversità della Svizzera italiana (USI) (Switzerland) and Università degli Studi di Milano Bicocca (Italy)
Pre-print
12:20
10m
Talk
Discussion Period
Papers