Office: LAS 1012A
Lassonde School of Engineering
York University
Toronto, ON, Canada M3J 1P3

Phone: 416-736-2100 ext.33939

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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.

20th Sep. 2020:
One paper accepted to Water.


Lassonde, EECS
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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.

Looking for hard-working students
I have several cool projects, and I am looking for hard-working students to drive them! Email me if you're interested in working with me. More details are here Opportunities.

Selected Publications (Full List)

  • 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)

  • 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

  • Machine Learning-Based Water Level Prediction in Lake Erie
    Qi Wang and Song Wang
    Water 2020

  • 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)