About Me

protrait

Yongqiang TIAN (田 永强)

HKUST Email: yqtian [-AT-] ust.hk

I am a Post-doctoral Fellow at CASTLE group of HKUST, working with Prof. Shing-Chi CHEUNG. Piror to that, I am a Ph.D. student at both HKUST and UWaterloo, co-supervised by Prof. Shing-Chi CHEUNG and Prof. Chengnian SUN. My research interest lies in software testing and debugging, especially the automated techniques for Deep Learning systems, Compilers and so on.


Updates

  • Jul, 2023: I passed my Ph.D. defense. Thanks for the support from my supervisors, labmates, collaborators and families.
  • Jul, 2023: Paper On the Caching Schemes to Speed Up Program Reduction is accepted by TOSEM.
  • May, 2023: Paper Revisiting the Evaluation of Deep Learning-Based Compiler Testing is accepted by IJCAI.
  • May, 2023: Paper PPR: Pairwise Program Reduction is accepted by ESEC/FSE.
  • Mar, 2023: Two papers, CoopHance: Cooperative Enhancement for Robustness of Deep Learning Systems and Fuzzing Deep Learning Compilers with HirGen are accepted by ISSTA.

Education

  • The Hong Kong University of Science and Technology Sep, 2017 - Jul, 2023    
    University of Waterloo, Canada Sep, 2020 - Jul, 2023    
    Dual Ph.D. Program in Computer Science.
    Supervised by Prof. Shing-Chi CHEUNG and Prof. Chengnian Sun
  • City University of Hong Kong Sep, 2013 - Jul, 2017   
    B.Eng. in Information Engineering (First Class Hornors)
  • University College London, United Kingdom Sep, 2015 - Dec, 2015   
    Exchange Student in Department of Computer Science

Publications (Google Scholar, DBLP)

  1. [TOSEM'23] On the Caching Schemes to Speed Up Program Reduction.
    Yongqiang Tian, Xueyan Zhang, Yiwen Dong, Zhenyang Xu, Mengxiao Zhang, Yu Jiang, Shing-Chi Cheung, Chengnian Sun
    in ACM Transactions on Software Engineering and Methodology (TOSEM), to Appear, 2023.
  2. [TOSEM'23] Finding Deviated Behaviors of the Compressed DNN Models for Image Classifications.
    Yongqiang Tian, Wuqi Zhang, Ming Wen, Shing-Chi Cheung, Chengnian Sun, Shiqing Ma, Yu Jiang
    in ACM Transactions on Software Engineering and Methodology (TOSEM), to Appear, 2023.
  3. [IJCAI'23] Revisiting the Evaluation of Deep Learning-Based Compiler Testing.
    Yongqiang Tian, Zhenyang Xu, Yiwen Dong, Chengnian Sun, Shing-Chi Cheung
    in The 32nd International Joint Conference on Artificial Intelligence (IJCAI-23), to Appear, 2023.
  4. [ESEC/FSE'23 Tool] Ad Hoc Syntax-Guided Program Reduction..
    Jia Le Tian, Mengxiao Zhang, Zhenyang Xu, Yongqiang Tian, Yiwen Dong, Chengnian Sun (2023).
    in ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, to Appear, 2023.
  5. [ESEC/FSE'23] PPR: Pairwise Program Reduction.
    Mengxiao Zhang, Zhenyang Xu, Yongqiang Tian, Yu Jiang, Chengnian Sun
    in ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, to Appear, 2023.
  6. [ISSTA'23] CoopHance: Cooperative Enhancement for Robustness of Deep Learning Systems.
    Quan Zhang, Yongqiang Tian, Yifeng Ding, Shanshan Li, Chengnian Sun, Yu Jiang, Jiaguang Sun
    in ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), to Appear, 2023.
  7. [ISSTA'23] Fuzzing Deep Learning Compilers with HirGen.
    Haoyang Ma, Qingchao Shen, Yongqiang Tian, Junjie Chen, Shing-Chi Cheung
    in ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), to Appear, 2023.
  8. [TOSEM'23] COMET: Coverage-guided Model Generation For Deep Learning Library Testing.
    Meiziniu Li, Jialun Cao, Yongqiang Tian, Tsz On Li, Ming Wen, Shing-Chi Cheung.
    in ACM Transactions on Software Engineering and Methodology (TOSEM), to Appear, 2023.
  9. [OOPSLA'23] Pushing the Limit of 1-Minimality of Language-Agnostic Program Reduction.
    Zhenyang Xu, Yongqiang Tian, Mengxiao Zhang, Gaosen Zhao, Yu Jiang, Chengnian Sun
    in the ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA), to Appear, 2023.
  10. [ASPLOS'23] Compilation Consistency Modulo Debug Information.
    Theodore Luo Wang, Yongqiang Tian, Yiwen Dong, Zhenyang Xu, Chengnian Sun
    in the 28th Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'23), to Appear, 2023.
  11. [SCIS'23] Towards Actionable Testing of Deep Learning Models.
    Yingfei Xiong, Yongqiang Tian, Yepang Liu, Shing-Chi Cheung
    in Science China Information Sciences, to Appear, 2023.
  12. [TOSEM'22] Bash in the Wild: Language Usage, Code Smells, and Bugs.
    Yiwen Dong, Zheyang Li, Yongqiang Tian, Chengnian Sun, Michael Godfrey, Meiyappan Nagappan
    in ACM Transactions on Software Engineering and Methodology, to Appear, 2022.
  13. [ICSE'22] SnR: Constraint-Based Type Inference for Incomplete Java Code Snippets.
    Yiwen Dong, Tianxiao Gu, Yongqiang Tian, Chengnian Sun
    in 44th International Conference on Software Engineering, Pittsburgh, PA, USA, May 2022.
  14. [ICSE'22] DeepFD: Automated Fault Diagnosis and Localization for Deep Learning Programs.
    Jialun Cao, Meiziniu LI, Xiao Chen, Ming Wen, Yongqiang Tian, Bo Wu, Shing-Chi Cheung
    in 44th International Conference on Software Engineering, Pittsburgh, PA, USA, May 2022.
  15. [EMSE'21, ICSE'22 Journal-first] To What Extent Do DNN-based Image Classification Models Make Unreliable Inferences?
    Yongqiang Tian, Shiqing Ma, Ming Wen, Yepang Liu, Shing-Chi Cheung, Xiangyu Zhang
    in Empirical Software Engineering, 26, Article number: 84, 2021. [Paper] [Website] [bib]
  16. [ESEC/FSE'21] A Comprehensive Study of Deep Learning Compiler Bugs.
    Qingchao Shen, Haoyang Ma, Junjie Chen, Yongqiang Tian, Shing-Chi Cheung, Xiang Chen
    in The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), Virtual, Aug 2021 (Acceptance ratio 24.5%=97/396)
  17. [ISSTA'21] AdvDoor: Adversarial Backdoor Attack of Deep Learning System.
    Quan Zhang, Yifeng Ding, Yongqiang Tian, Jianmin Guo, Min Yuan, Yu Jiang
    in ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), Virtual, July 2021 (Acceptance ratio 21.9%=51/233)
  18. [ICSE'20 Demo] EvalDNN: A Toolbox for Evaluating Deep Neural Network Models.
    Yongqiang Tian, Zhihua Zeng, Ming Wen, Yepang Liu, Tzu-yang Kuo, Shing-Chi Cheung
    in The 42nd International Conference on Software Engineering (ICSE 2020 Demos), Virtual, May 2020
    Project website, Demo video.
  19. [TSE] Historical Spectrum based Fault Localization.
    Ming Wen, Junjie Chen, Yongqiang Tian, Rongxin Wu, Dan Hao, Shi Han, Shing-Chi Cheung
    in IEEE Transactions on Software Engineering (Volume: 47, Issue: 11, Nov. 1 2021)
  20. [arXiv] Testing Deep Learning Models for Image Analysis Using Object-Relevant Metamorphic Relations.
    Yongqiang Tian, Shiqiang Ma, Ming Wen, Yepang Liu, Shing-Chi Cheung, Xiangyu Zhang.
    Note: A later version is accepted by EMSE in 2021.
  21. [ESEC/FSE’19] Exploring and Exploiting the Correlations between Bug-Inducing and Bug-Fixing Commits.
    Ming Wen, Rongxin Wu, Yepang Liu, Yongqiang Tian, Xuan Xie, Shing-Chi Cheung and Zhendong Su
    In The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Technical Research Paper, Tallinn, Estonia, 2019 (Acceptance ratio 24.4%=74/303)
  22. [CAN Workshop’17] Unveiling Performance of NFV Software Dataplanes.
    Zhixiong Niu, Hong Xu, Libin Liu, Yongqiang Tian, Peng Wang, Zhenhua Li.
    CAN Workshop, co-located with ACM CoNEXT’ 17. Incheon, Republic of Korea. Dec, 2017.
  23. [IEEE Sarnoff Symposium’16] Kuijia: Traffic rescaling in data center WANs.
    Che Zhang, Hong Xu, Libin Liu, Zhixiong Niu, Peng Wang, Yongqiang Tian, Chengchen Hu.
    37th IEEE Sarnoff Symposium. Newark, NJ. Sept, 2016.

Teaching

  1. UWaterloo SE465 Software Testing and Quality Assurance, Winter 2023. Teaching Assistant.
  2. UWaterloo SE463 Software Requirements Specification & Analysis, Spring 2022. Teaching Assistant.
  3. UWaterloo SE490 Design Project 1, Spring 2022. Teaching Assistant.
  4. UWaterloo SE465 Software Testing and Quality Assurance, Winter 2022. Teaching Assistant.
  5. HKUST COMP5111 Fundamentals of Software Analysis, Spring 2020. Teaching Assistant.
  6. HKUST COMP5111 Fundamentals of Software Analysis, Spring 2019. Teaching Assistant.
  7. HKUST COMP3021 Java Programming, Fall 2018. Teaching Assistant.
  8. CityU EE3201 Signals and Systems, Fall 2016. Student Tutor

Academic Service

  1. Program Committee, ICST'24
  2. Journal Reviewer, TOSEM, TDSC
  3. Artifact Evaluation Committee, PLDI'23, ISSTA'23, ESEC/FSE'23
  4. Shadow PC, MSR'22
  5. Additional Reviewers within the Technical Track-track, ICSE'21, ISSTA'21, ESEC/FSE'22
  6. Student Volunteer, ISSTA'19

Voluntary Experience

  1. Volunteer of City-Youth Empowerment Project, CityU of HK, Fall 2016

Honors and Awards

  1. ASPLOS'23 Student Travel Grant, 2023.
  2. GO-Bell Scholarships, University of Waterloo, 2020-2022.
  3. Microsoft Asia Cloud Research Software Fellow (CRSF) Awards, 2019.
  4. Hong Kong PhD Fellowship Scheme, Research Grants Council (RGC) of Hong Kong, Annually (2017-2020).
  5. Bronze Award and Innovative Idea Award, CityU EE Information Product Design Competition, May 2016.
  6. Dean’s List, College of Science and Engineering, CityU, 7 times in 2013-2017.
  7. Mainland Student Scholarship, CityU, 2013-2017.
  8. Outstanding Student Prize, CityU EE, June 2014.
  9. Champion in Junior Group, CityU CS Programming, 2014.
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