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ICSE 2021
Mon 17 May - Sat 5 June 2021
Thu 27 May 2021 21:10 - 21:30 at Blended Sessions Room 3 - 3.6.3. Fault Localization #2 Chair(s): Davide Falessi
Fri 28 May 2021 09:10 - 09:30 at Blended Sessions Room 3 - 3.6.3. Fault Localization #2

Performance issues may compromise user experiences, increase the cost resources, and cause field failures. One of the most prevalent performance issues is performance regression. Due to the importance and challenges in performance regression detection, prior research proposes various automated approaches that detect performance regressions. However, the performance regression detection is conducted after the system is built and deployed. Hence, large amounts of resources are still required to locate and fix performance regressions. In our paper, we propose an approach that automatically predicts whether a test would manifest performance regressions given a code commit. In particular, we extract both traditional metrics and performance-related metrics from the code changes that are associated with each test. For each commit, we build random forest classifiers that are trained from all prior commits to predict in this commit whether each test would manifest performance regression. We conduct case studies on three open-source systems (Hadoop, Cassandra and OpenJPA). Our results show that our approach can predict tests that manifest performance regressions in a commit with high AUC values (on average 0.86). Our approach can drastically reduce the testing time needed to detect performance regressions. In addition, we find that our approach could be used to detect the introduction of six out of nine real-life performance issues from the subject systems during our studied period. Finally, we find that traditional metrics that are associated with size and code change histories are the most important factors in our models. Our approach and the study results can be leveraged by practitioners to effectively cope with performance regressions in a timely and proactive manner.

Thu 27 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

20:50 - 21:50
3.6.3. Fault Localization #2SEIP - Software Engineering in Practice / Technical Track / Journal-First Papers at Blended Sessions Room 3 +12h
Chair(s): Davide Falessi California Polytechnic State University
20:50
20m
Paper
Fault Localization with Code Coverage Representation LearningTechnical Track
Technical Track
Yi Li New Jersey Institute of Technology, Shaohua Wang New Jersey Institute of Technology, Tien N. Nguyen University of Texas at Dallas
Pre-print Media Attached
21:10
20m
Paper
PerfJIT: Test-level Just-in-time Prediction for Performance Regression Introducing CommitsJournal-First
Journal-First Papers
Jinfu Chen Centre for Software Excellence, Huawei, Canada, Weiyi Shang Concordia University, Emad Shihab Concordia University
Link to publication Pre-print Media Attached
21:30
20m
Paper
Scalable Statistical Root Cause Analysis on App TelemetrySEIP
SEIP - Software Engineering in Practice
Vijayaraghavan Murali Facebook, Inc., Edward Yao Facebook, Umang Mathur University of Illinois at Urbana-Champaign, Satish Chandra Facebook, USA
Pre-print Media Attached

Fri 28 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

08:50 - 09:50
08:50
20m
Paper
Fault Localization with Code Coverage Representation LearningTechnical Track
Technical Track
Yi Li New Jersey Institute of Technology, Shaohua Wang New Jersey Institute of Technology, Tien N. Nguyen University of Texas at Dallas
Pre-print Media Attached
09:10
20m
Paper
PerfJIT: Test-level Just-in-time Prediction for Performance Regression Introducing CommitsJournal-First
Journal-First Papers
Jinfu Chen Centre for Software Excellence, Huawei, Canada, Weiyi Shang Concordia University, Emad Shihab Concordia University
Link to publication Pre-print Media Attached
09:30
20m
Paper
Scalable Statistical Root Cause Analysis on App TelemetrySEIP
SEIP - Software Engineering in Practice
Vijayaraghavan Murali Facebook, Inc., Edward Yao Facebook, Umang Mathur University of Illinois at Urbana-Champaign, Satish Chandra Facebook, USA
Pre-print Media Attached