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MSR 2021
Mon 17 - Wed 19 May 2021
co-located with ICSE 2021

Software debugging, and program repair are among the most time-consuming and labor-intensive tasks in software engineering that would benefit a lot from automation. In this paper, we propose a novel automated program repair approach based on CodeBERT, which is a transformer-based neural architecture pre-trained on large corpus of source code. We fine-tune our model on the ManySStuBs4J small and large datasets to automatically generate the fix codes. The results show that our technique accurately predicts the fixed codes implemented by the developers in 19-72% of the cases, depending on the type of datasets, in less than a second per bug. We also observe that our method can generate varied-length fixes (short and long) and can fix different types of bugs, even if only a few instances of those types of bugs exist in the training dataset.

Conference Day
Mon 17 May

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

17:00 - 17:50
Mining Challenge SessionMining Challenge / Technical Papers at MSR Room 1
Chair(s): Charles SuttonGoogle Research, Rafael-Michael KarampatsisThe University of Edinburgh, Miltiadis AllamanisMicrosoft Research, UK
17:01
2m
Welcome by the Mining Challenge Co-chairs
Mining Challenge
Miltiadis AllamanisMicrosoft Research, UK, Rafael-Michael KarampatsisThe University of Edinburgh, Charles SuttonGoogle Research
17:03
3m
Talk
A large-scale study on human-cloned changes for automated program repair
Mining Challenge
Fernanda MadeiralKTH Royal Institute of Technology, Thomas DurieuxKTH Royal Institute of Technology, Sweden
Link to publication Pre-print
17:06
3m
Talk
Applying CodeBERT for Automated Program Repair of Java Simple Bugs
Mining Challenge
Ehsan MashhadiUniversity of Calgary, Hadi HemmatiUniversity of Calgary
Pre-print Media Attached
17:09
3m
Talk
PySStuBs: Characterizing Single-Statement Bugs in Popular Open-Source Python Projects
Mining Challenge
Arthur Veloso KamienskiUniversity of Alberta, Luisa PalechorUniversity of Alberta, Abram HindleUniversity of Alberta, Cor-Paul BezemerUniversity of Alberta
Pre-print
17:12
3m
Talk
How Effective is Continuous Integration in Indicating Single-Statement Bugs?
Mining Challenge
Jasmine LatendresseConcordia University, Rabe AbdalkareemQueens University, Kingston, Canada, Diego CostaConcordia University, Canada, Emad ShihabConcordia University
Pre-print
17:15
3m
Talk
Mea culpa: How developers fix their own simple bugs differently from other developers
Mining Challenge
Wenhan ZhuUniversity of Waterloo, Michael W. GodfreyUniversity of Waterloo, Canada
Pre-print
17:18
3m
Talk
On the Distribution of "Simple Stupid Bugs" in Unit Test Files: An Exploratory Study
Mining Challenge
Anthony PerumaRochester Institute of Technology, Christian D. NewmanRochester Institute of Technology
Pre-print Media Attached
17:21
3m
Talk
On the Rise and Fall of Simple Stupid Bugs: a Life-Cycle Analysis of SStuBs
Mining Challenge
Balázs MosolygóUniversity of Szeged, Norbert VándorUniversity of Szeged, Gabor AntalUniversity of Szeged, Peter HegedusUniversity of Szeged
Pre-print
17:24
3m
Talk
On the Effectiveness of Deep Vulnerability Detectors to Simple Stupid Bug Detection
Mining Challenge
Jiayi HuaBeijing University of Posts and Telecommunications, Haoyu WangBeijing University of Posts and Telecommunications
Pre-print
17:27
23m
Live Q&A
Discussions and Q&A
Technical Papers


Information for Participants
Info for MSR Room 1: