MSR 2024
Mon 15 - Tue 16 April 2024 Lisbon, Portugal
co-located with ICSE 2024
Mon 15 Apr 2024 11:48 - 11:52 at Grande Auditório - Defects, Bugs and Issues Chair(s): Wesley Assunção

We call a program that passes existing tests but still contains bugs as a buggy plausible program. Bugs in such a program can bypass the testing environment and enter the production environment, causing unpredictable consequences. Therefore, discovering and fixing such bugs is a fundamental and critical problem. However, no existing bug dataset is purposed to collect this kind of bug, posing significant obstacles to relevant research. To address this gap, we introduce TrickyBugs, a bug dataset with 3,043 buggy plausible programs sourced from human-written submissions of 324 real-world competition coding tasks. We identified the buggy plausible programs from approximately 400,000 submissions, and all the bugs in TrickyBugs were not previously detected. We hope that TrickyBugs can effectively facilitate research in the fields of automated program repair, fault localization, test generation, and test adequacy.

Mon 15 Apr

Displayed time zone: Lisbon change

11:00 - 12:30
11:00
12m
Talk
Enhancing Performance Bug Prediction Using Performance Code Metrics
Technical Papers
Guoliang Zhao Computer Science of Queen's University, Stefanos Georgio , Safwat Hassan University of Toronto, Canada, Ying Zou Queen's University, Kingston, Ontario, Derek Truong IBM Canada, Toby Corbin IBM UK
11:12
12m
Talk
CrashJS: A NodeJS Benchmark for Automated Crash Reproduction
Technical Papers
Philip Oliver Victoria University of Wellington, Jens Dietrich Victoria University of Wellington, Craig Anslow Victoria University of Wellington, Michael Homer Victoria University of Wellington
11:24
12m
Talk
An Empirical Study on Just-in-time Conformal Defect Prediction
Technical Papers
Xhulja Shahini paluno - University of Duisburg-Essen, Andreas Metzger University of Duisburg-Essen, Klaus Pohl
11:36
12m
Talk
Fine-Grained Just-In-Time Defect Prediction at the Block Level in Infrastructure-as-Code (IaC)
Technical Papers
Mahi Begoug , Moataz Chouchen ETS, Ali Ouni ETS Montreal, University of Quebec, Eman Abdullah AlOmar Stevens Institute of Technology, Mohamed Wiem Mkaouer University of Michigan - Flint
11:48
4m
Talk
TrickyBugs: A Dataset of Corner-case Bugs in Plausible Programs
Data and Tool Showcase Track
Kaibo Liu Peking University, Yudong Han Peking University, Yiyang Liu Peking University, Zhenpeng Chen Nanyang Technological University, Jie M. Zhang King's College London, Federica Sarro University College London, Gang Huang Peking University, Yun Ma Peking University
11:52
4m
Talk
GitBugs-Java: A Reproducible Java Benchmark of Recent Bugs
Data and Tool Showcase Track
André Silva KTH Royal Institute of Technology, Nuno Saavedra INESC-ID and IST, University of Lisbon, Martin Monperrus KTH Royal Institute of Technology
11:56
4m
Talk
A Dataset of Partial Program Fixes
Data and Tool Showcase Track
Dirk Beyer LMU Munich, Lars Grunske Humboldt-Universität zu Berlin, Matthias Kettl LMU Munich, Marian Lingsch-Rosenfeld LMU Munich, Moeketsi Raselimo Humboldt-Universität zu Berlin
12:00
4m
Talk
BugsPHP: A dataset for Automated Program Repair in PHP
Data and Tool Showcase Track
K.D. Pramod University of Moratuwa, Sri Lanka, W.T.N. De Silva University of Moratuwa, Sri Lanka, W.U.K. Thabrew University of Moratuwa, Sri Lanka, Ridwan Salihin Shariffdeen National University of Singapore, Sandareka Wickramanayake University of Moratuwa, Sri Lanka
Pre-print
12:04
4m
Talk
AW4C: A Commit-Aware C Dataset for Actionable Warning Identification
Data and Tool Showcase Track
Zhipeng Liu , Meng Yan Chongqing University, Zhipeng Gao Shanghai Institute for Advanced Study - Zhejiang University, Dong Li , Xiaohong Zhang Chongqing University, Dan Yang Chongqing University
12:08
5m
Talk
Predicting the Impact of Crashes Across Release Channels
Industry Track
Suhaib Mujahid Mozilla, Diego Costa Concordia University, Canada, Marco Castelluccio Mozilla
12:13
5m
Talk
Zero Shot Learning based Alternatives for Class Imbalanced Learning Problem in Enterprise Software Defect Analysis
Industry Track
Sangameshwar Patil Dept. of CSE, IIT Madras and TRDDC, TCS, B Ravindran IITM