👋Welcome！
I am Ming Yan, a SE Ph.D. candidate at College of Intelligence and Computing, Tianjin University, supervised by Prof. Junjie Chen. I received my master’s degree in 2021 and bachelor’s degree in 2018 both from Tianjin University supervised by Prof. Zan Wang. My research interests lie primarily in DL system quality assurance and software testing.
📢 I anticipate earning my Ph.D. by July 2025 and am actively seeking opportunities in academia or industry. Please feel free to contact me.
Find my CV (in English) | 简历（中文）
Email: yanming[at]tju[DOT]edu[DOT]cn
Address: Building #55, College of Intelligence and Computing, Tianjin University Beiyangyuan Campus, No. 135 Yaguan Road, Jinnan District, Tianjin, 300350
News
📢 Jun 9, 2024: I have been selected as a member of the ISSRE 2024 Artifact Evaluation Committee. Thanks for the recognition!
📢 Jan 6, 2024: I have been selected as a member of the ECOOP 2024 Artifact Evaluation Committee. Thanks for the recognition!
📢 Dec 3, 2023: I have been selected as a member of the CCF ChinaSoft (2023) Outstanding Ph.D. Student Forum!
📢 Oct 20, 2023: I received the Outstanding Contribution Award from the Huawei-Tianjin University Artificial Intelligence Innovation Lab for the deployment of the LMT technique in six Huawei chip design modules. Thanks for the recognition!
📢 Sep 8, 2023: Our paper “Stratified random sampling for neural network test input selection” was accepted by IST. Congrats to Zhuo!
Jul 25, 2023: Our paper “Test Case Selection for Deep Neural Networks via Data Mutation” was accepted by Journal of Software. Congratulations to Xuejie!
Feb 19, 2023: Our paper “Revisiting Deep Neural Network Test Coverage from the Test Effectiveness Perspective” was accepted by Journal of Software: Evolution and Process.
Feb 16, 2023: I have been selected as a reviewer for the ISSTA 2023 Artifact Evaluation Committee. Thanks for the recognition!
Dec 22, 2022: Our paper “Achieving Last-Mile Functional Coverage in Testing Chip Design Software Implementations” was accepted by ICSE 2023 SEIP track. This work was done during my internship at Noah’s Ark Lab (Beijing). Thanks for the recognition!
Jul 9, 2022: Our paper “An Empirical Study on Numerical Bugs in Deep Learning Programs” was accepted by ASE 2022 NIER track. Congratulations to Gan!
Jun 18, 2021: Our TOSEM paper “Practical Accuracy Estimation for Efficient Deep Neural Network Testing” was accepted as a Journal-First paper for presentation at FSE 2021. Thanks for the recognition!
May 20, 2021: Our paper “Exposing Numerical Bugs in Deep Learning via Gradient Back-propagation” was accepted by ESEC/FSE 2021.
May 20, 2021: I will join Noah’s Ark Lab (Beijing) as an intern.
Aug 21, 2020: Our paper “Deep Learning Library Testing via Effective Model Generation” won the ACM SIGSOFT Distinguished Paper Award at ESEC/FSE 2020. Thanks for the recognition!
May 20, 2020: Our paper “Deep Learning Library Testing via Effective Model Generation” was accepted by ESEC/FSE 2020.
May 1, 2020: Our paper “Survey on testing of deep neural networks” was published in Journal of Software.
March 26, 2020: Our research paper “Practical Accuracy Estimation for Efficient Deep Neural Network Testing” was accepted by TOSEM.
Publications
† : refers to the first student author, * : refers to the corresponding author.
1. [IST'23] Stratified random sampling for neural network test input selection. (CCF-B)
Zhuo Wu, Zan Wang, Junjie Chen, Hanmo You, Ming Yan, Lanjun Wang*.
In: Information and Software Technology, 2023, to appear.
2. [Journal of Software'23] Test Case Selection for Deep Neural Networks via Data Mutation. (CCF-B)
Xuejie Cao, Junjie Chen*, Ming Yan, Hanmo You , Zhuo Wu, Zan Wang.
In: Journal of Software (in Chinese), 2023, to appear.
3. [JSEP'23] Revisiting Deep Neural Network Test Coverage from the Test Effectiveness Perspective. (CCF-B)
Ming Yan, Junjie Chen*, Xuejie Cao, Zhuo Wu, Yuning Kang, Zan Wang.
In: Journal of Software: Evolution and Process, 2023, pages to appear.
4. [ICSE-SEIP'23] Achieving Last-Mile Functional Coverage in Testing Chip Design Software Implementations. (CCF-A)
Ming Yan, Junjie Chen*, Hangyu Mao, Jiajun Jiang, Jianye Hao, Xingjian Li, Zhao Tian, Zhichao Chen, Dong Li, Zhangkong Xian, Yanwei Guo, Wulong Liu, Bin Wang, Yuefeng Sun, Yongshun Cui.
In: The 45th International Conference on Software Engineering, SEIP track, May 14-20, 2023, pages to appear, Melbourne Convention and Exhibition Centre, Melbourne, Australia.
5. [ASE-NIER'22] An Empirical Study on Numerical Bugs in Deep Learning Programs.
Gan Wang, Zan Wang, Junjie Chen*, Xiang Chen, Ming Yan.
In: The 37th IEEE/ACM International Conference on Automated Software Engineering, NIER track, October 10-14, 2022, pages to appear, Oakland Center, Michigan, USA
6. [FSE'21] Exposing Numerical Bugs in Deep Learning via Gradient Back-propagation. (CCF-A)
Ming Yan, Junjie Chen*, Xiangyu Zhang, Lin Tan, Gan Wang, Zan Wang.
In: The 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, August 23-28, 2021, 627-638, Athens, Greece
ACM SIGSOFT Distinguished Paper Award Nominee
7. [FSE'20] Deep Learning Library Testing via Effective Model Generation. (CCF-A)
Zan Wang, Ming Yan†, Junjie Chen*, Shuang Liu, Dongdi Zhang.
In: The 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, November 8-13, 2020, 788-799, Sacramento, California, United States
🏆 ACM SIGSOFT Distinguished Paper Award
8. [Journal of Software'20] Survey on testing of deep neural networks. (CCF-B)
Zan Wang, Ming Yan†, Shuang Liu*, Junjie Chen, Dongdi Zhang, Zhuo Wu, Xiang Chen.
In: Journal of Software, 2020,31(5):1255−1275 (in Chinese).
9. [TOSEM'20] Practical Accuracy Estimation for Efficient Deep Neural Network Testing.(CCF-A)
Junjie Chen, Zhuo Wu, Zan Wang, Hanmo You, Lingming Zhang, Ming Yan.
In: ACM Transactions on Software Engineering and Methodology (TOSEM),2020, 29(4): 1-35., (Selected for ESEC/FSE 2021 Journal-First Presentation)
Academic Services
Reviewer
◆ 2024: ISSRE Artifact Evaluation Committee
◆ 2024: ECOOP Artifact Evaluation Committee
◆ 2023: ISSTA Artifact Evaluation Committee
Co-Reviewer
◆ 2024: ISSTA co-reviewer
◆ 2023: ESEC/FSE co-reviewer, ASE co-reviewer, ICSE(2024) co-reviewer
◆ 2022: ESEC/FSE co-reviewer, ASE co-reviewer
◆ 2021: ISSTA co-reviewer, TDSC co-reviewer.
◆ 2020: ISSTA Tool Demo co-reviewer, JCST co-reviewer, COMPSAC co-reviewer, Journal of Software co-reviewer.
Talks
Achieving Last-Mile Functional Coverage in Testing Chip Design Software Implementations. May. 2023
◆ ICSE 2023 Conference Talk.
◆ Melbourne, Australia.
Revisiting Deep Neural Network Test Coverage from the Test Effectiveness Perspective. Nov. 2022
◆ ChinaSoft 2022 Conference Talk.
◆ Virtual Event.
Exposing numerical bugs in deep learning via gradient back-propagation. Aug. 2021
◆ ESEC/FSE 2021 Conference Talk.
◆ Virtual Event.
Deep Learning Library Testing via Effective Model Generation. Nov. 2020
◆ ESEC/FSE 2020 Conference Talk.
◆ Virtual Event. [Video]
Survey on testing of deep neural networks. Dec. 2019
◆ NASAC 2019 Conference Talk. Hangzhou, China
Honors & Awards
- 2024: Huawei Scholarship, Huawei
- 2023: Outstanding Ph.D Student Forum, CCF ChinaSoft
- 2023: Huawei: Outstanding Contribution Award, Huawei & Tianjin University
- 2022: CIE Outstanding Master Dissertation Award, Chinese Institute of Electronics
- 2021: Outstanding Graduate Students, Tianjin University (master’s degree)
- 2021: Outstanding Master Dissertation Award, Tianjin University
- 2020: National Scholarship, Ministry of Education
- 2020: Innovation Scholarship, College of Intelligence and Computing, Tianjin University
- 2020: ACM SIGSOFT Distinguished Paper Award
- 2018: Outstanding Graduate Students, Tianjin University (bachelor’s degree)
