Office: LAS 1012A
Lassonde School of Engineering
York University
Toronto, ON, Canada M3J 1P3
Phone: 416-736-2100 ext.33939
Email: wangsong@yorku.ca
5th Dec. 2023:
our APSEC'23 paper won a Distinguished Paper Award.
9th Oct. 2023:
Moshi's paper is accepted to ICSE'24 (Second Cycle).
6th Oct. 2023:
Jiho's paper is accepted to TOSEM.
24th August. 2023:
One paper accepted to ICSE'24 (First Cycle).
23th August. 2023:
Jiho's paper is accepted to APSEC'23.
29th July. 2023:
Niam's paper is accepted to ISSRE'23.
15th March. 2023:
Niam's paper is accepted to MSR'23.
9th Dec. 2022:
Two papers accepted to ICSE'23.
Nov. 2022:
Will serve on program committee of CAIN'23 and MSR'23
8th Sept. 2022:
One paper accepted to IEEE TR.
28th July. 2022:
Our Arun has successfully defended his master's thesis!
20th July. 2022:
One paper accepted to ASE 2022.
July. 2022:
Will serve on program committee of ESEC/FSE'23, SANER'23 , and ICSE'23 Demo.
5th July. 2022:
One paper accepted to IST.
Lassonde,
EECS
Gradudate Application
Top SE Conferences
Top SE Journals
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 Artificial Intelligence. More specifically, my research focuses on 1) taking advantage of AI technologies to address challenging issues of software reliability practices (AI for SE) and 2) developing software reliability assurance techniques to improve the reliability and security of AI infrastructure systems (SE for AI). 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.
Demystifying and Detecting Misuses of Deep Learning APIs
Moshi Wei, Nima Shiri Harzevili, Yuekai Huang, Jinqiu Yang, Junjie Wang, and Song Wang
ICSE 2024
PDF
The Good, the Bad, and the Missing: Neural Code Generation for Machine Learning Tasks
Jiho Shin, Moshi Wei, Junjie Wang, Lin Shi, and Song Wang
ACM Transactions on Software Engineering and Methodology (TOSEM'23)
PDF
An Empirical Study on the Stability of Explainable Software Defect Prediction
Jiho Shin, Reem Aleithan, Jaechang Nam, Junjie Wang, Nima Shiri Harzevili and Song Wang
APSEC 2023 (acceptance rate=33% 43/128)
PDF
Distinguished Paper Award
Automatic Static Vulnerability Detection for Machine Learning Libraries: Are We There Yet?
Nima Shiri Harzevili, Jiho Shin, Junjie Wang, Song Wang, and Nachiappan Nagappan
ISSRE 2023 (acceptance rate=25% 62/247)
PDF
Characterizing and Understanding Software Security Vulnerabilities in Machine Learning Libraries
Nima Shiri Harzevili, Jiho Shin, Junjie Wang, Song Wang, and Nachiappan Nagappan
MSR 2023 (acceptance rate=37% 43/115)
PDF
Developer-Intent Driven Code Comment Generation
Fangwen Mu, Xiao Chen, Lin Shi, Song Wang, and Qing Wang
ICSE 2023 (acceptance rate=26% 209/796)
PDF
CoCoFuzzing: Testing Neural Code Models with Coverage-Guided Fuzzing
Moshi Wei, Yuchao Huang, Jinqiu Yang, Junjie Wang, and Song Wang
IEEE Transactions on Reliability (TR'22)
PDF
Automatic Comment Generation via Multi-Pass Deliberation
Fangwen Mu, Xiao Chen, Lin Shi, Song Wang, and Qing Wang
ASE 2022 (acceptance rate=22% 116/525)
PDF
API Recommendation for Machine Learning Libraries: How Far Are We?
Moshi Wei, Yuchao Huang, Junjie Wang, Jiho Shin, Shiri harzevili Nima, and Song Wang
ESEC/FSE 2022 (acceptance rate=22% 99/449)
PDF
Are We Building on the Rock? On the Importance of Data Preprocessing for Code Summarization
Lin Shi, Fangwen Mu, Xiao Chen, Song Wang, Junjie Wang, Ye Yang, Ge Li, Xin Xia, and Qing Wang
ESEC/FSE 2022 (acceptance rate=22% 99/449)
PDF
CLEAR: Contrastive Learning for API Recommendation
Moshi Wei, Shiri harzevili Nima, Yuchao Huang, Junjie Wang, and Song Wang
ICSE 2022 (acceptance rate=26% 197/751)
PDF
Find Bugs in Static Bug Finders
Junjie Wang, Yuchao Huang, Song Wang, and Qing Wang
ICPC 2022 (acceptance rate=41% 41/102)
ACM SIGSOFT Distinguished Paper Award
PDF
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)
PDF
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)
PDF
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
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Large-Scale Intent Analysis for Identifying Large-Review-Effort Code Changes
Song Wang, Chetan Bansal, and Nachiappan Nagappan
Information and Software Technology 2020
PDF
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
PDF
Deep Semantic Feature Learning for Software Defect Prediction
Song Wang, Taiyue Liu, Jaechang Nam, and Lin Tan
IEEE Transaction on Software Engineering 2018
PDF