Office: LAS 1012A
Lassonde School of Engineering
Toronto, ON, Canada M3J 1P3
Phone: 416-736-2100 ext.33939
20th Sept. 2021:
One paper accepted to TOSEM.
8th August. 2021:
I will serve on program committee of MSR'22.
30th July. 2021:
One paper accepted to ISSRE'21.
15th July. 2021:
One paper accepted to Applied Sciences.
30th June. 2021:
Two papers accepted to ESEM'21.
27th May. 2021:
Reem got the first place at the ACM Student Research Competition @ ICSE'21.
2nd May. 2021:
One paper accepted to TSE.
15th April. 2021:
I get TOSEM Distinguished Reviewer Award TOSEM.
15th Dec. 2020:
One paper accepted to ICSE'21.
15th Nov. 2020:
I will serve on program committee of ICSE'22.
I am an Assistant Professor at the Department of Electrical Engineering and Computer Science at York University. I work at the intersection of Software Engineering and Machine Learning. More specifically, my research work focuses on taking the advantages of ML techniques in data process, knowledge representation, classification, NLP, etc., to address challenging issues of software reliability practices. My research interests include software engineering, software reliability, program analysis, software testing, and machine learning. The tools and techniques developed in my research have already helped detect hundreds of true bugs.
Automatic Unit Test Generation for Machine Learning Libraries: How Far Are We?
Song Wang, Nishtha Shrestha, Abarna Kucheri Subburaman, Junjie Wang, Moshi Wei, and Nachiappan Nagappan
ICSE 2021 (acceptance rate=22% 138/615)
Context- and Fairness-aware In-process Crowdworker Recommendation
Junjie Wang, Ye, Yang, Song Wang, Jun Hu, and Qing Wang
ACM Transactions on Software Engineering and Methodology (TOSEM'21)
Characterizing and Understanding Software Developer Networks in Security Development
Song Wang and Nachiappan Nagappan
ISSRE 2021 (acceptance rate=27% 52/189)
Continuous Software Bug Prediction
Song Wang, Junjie Wang, Jaechang Nam, and Nachiappan Nagappan
ESEM 2021 (acceptance rate=19% 24/124)
Context-aware Personalized Crowdtesting Task Recommendation
Junjie Wang, Ye Yang, Song Wang, Chunyang Chen, Dandan Wang, and Qing Wang
IEEE Transaction on Software Engineering 2021
Large-Scale Intent Analysis for Identifying Large-Review-Effort Code Changes
Song Wang, Chetan Bansal, and Nachiappan Nagappan
Information and Software Technology 2020
Context-aware In-process Crowdworker Recommendation
Junjie Wang, Ye Yang, Song Wang, Dandan Wang, and Qing Wang.
ICSE 2020 (acceptance rate=21% 129/617)
ACM SIGSOFT Distinguished Paper Award
Characterizing Crowds to Better Optimize Worker Recommendation in Crowdsourced Testing
Junjie Wang, Song Wang, Jianfeng Chen, Tim Menzies, Qiang Cui, Miao Xie, and Qing Wang.
IEEE Transaction on Software Engineering 2019
FSE 2019 Journal First
A Bug Finder Refined by a Large Set of Open-Source Projects
Jaechang Nam, Song Wang, Xi Yuan, and Lin Tan
Information and Software Technology 2019
Deep Semantic Feature Learning for Software Defect Prediction
Song Wang, Taiyue Liu, Jaechang Nam, and Lin Tan
IEEE Transaction on Software Engineering 2018
QTEP: Quality-aware Test Case Prioritization
Song Wang, Jaechang Nam, and Lin Tan
ESEC/FSE 2017 (acceptance rate=24% 72/295)
Automatically Learning Semantic Features for Defect Prediction
Song Wang, Taiyue Liu, and Lin Tan
ICSE 2016 (acceptance rate=19% 101/530)
Bugram: Bug Detection with N-gram Language Models
Song Wang, Devin Chollak, Dana Movshovitz-Attias, and Lin Tan
ASE 2016 (acceptance rate=19% 57/298)