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ICSE 2020
Wed 24 June - Thu 16 July 2020
Tue 7 Jul 2020 15:12 - 15:24 at Goguryeo - A2-Testing and Debugging 1 Chair(s): Na Meng

Understanding the root cause of a defect is critical to isolating and repairing buggy behavior. We present Causal Testing, a new method of root-cause analysis that relies on the theory of counterfactual causality to identify a set of executions that likely hold key causal information necessary to understand and repair buggy behavior. Using the Defects4J benchmark, we find that Causal Testing could be applied to 71% of real-world defects, and for 77% of those, it can help developers identify the root cause of the defect. A controlled experiment with 37 developers shows that Causal Testing improves participants’ ability to identify the cause of the defect from 80% of the time with standard testing tools to 86% of the time with Causal Testing. The participants report that Causal Testing provides useful information they cannot get using tools such as JUnit. Holmes, our prototype, open-source Eclipse plugin implementation of Causal Testing, is available at http://holmes.cs.umass.edu/.

Tue 7 Jul
Times are displayed in time zone: (UTC) Coordinated Universal Time change

15:00 - 15:12
Studying the Use of Java Logging Utilities in the WildTechnical
Technical Papers
Boyuan ChenYork University, Zhen Ming (Jack) JiangYork University
Authorizer link Pre-print
15:12 - 15:24
Causal Testing: Understanding Defects' Root CausesACM SIGSOFT Distinguished Artifact AwardsArtifact ReusableTechnicalArtifact Available
Technical Papers
Brittany JohnsonUniversity of Massachusetts Amherst, Yuriy BrunUniversity of Massachusetts Amherst, Alexandra MeliouUniversity of Massachusetts Amherst
Link to publication DOI Pre-print Media Attached
15:24 - 15:32
Studying the Characteristics of Logging Practices in Mobile Apps: A Case Study on F-Droid.J1
Journal First
Yi ZengConcordia University, Jinfu ChenConcordia University, Canada, Weiyi ShangConcordia University, Tse-Hsun (Peter) ChenConcordia University
Authorizer link Pre-print
15:32 - 15:38
Automatically Predicting Bug Severity Early in the Development ProcessNIER
New Ideas and Emerging Results
Jude ArokiamOntario Tech University, Jeremy BradburyOntario Tech University
15:38 - 15:46
A Survey on Adaptive Random TestingJ1
Journal First
Rubing HuangJiangsu University, Weifeng SunJiangsu University, Yinyin XuJiangsu University, Haibo ChenJiangsu University, Dave ToweyUniversity of Nottingham Ningbo China, Xin XiaMonash University
15:46 - 15:58
Code Level Model-Checking in the Software Development WorkflowArtifact ReusableArtifact AvailableSEIP
Software Engineering in Practice
Nathan ChongAmazon, Byron CookAmazon, Konstantinos KallasUniversity of Pennsylvania, Kareem KhazemAmazon, Felipe R. MonteiroAmazon, Daniel Schwartz-NarbonneAmazon, n.n., Serdar TasiranAmazon, n.n., Michael TautschnigAmazon Web Services, Mark R. TuttleAmazon
Pre-print Media Attached