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ORCIDYongqiang Tian 0001
Person information
- affiliation: University of Waterloo, Canada
- affiliation: Hong Kong University of Science and Technology, Hong Kong, SAR, China
Other persons with the same name
- Yongqiang Tian 0002
![[0009-0009-2404-4634]](https://dblp.org/img/orcid-mark.12x12.png "0009-0009-2404-4634")
— Alibaba Group, Beijing, China - Yongqiang Tian 0003 — Xiamen Environmental Monitoring Center Station in Fujian Province, China
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Journal Articles
- 2025
[j9]Weiqi Lu, Yongqiang Tian, Xiaohan Zhong, Haoyang Ma, Zhenyang Xu, Shing-Chi Cheung, Chengnian Sun:
An Empirical Study of Bugs in Data Visualization Libraries. Proc. ACM Softw. Eng. 2(FSE): 2075-2098 (2025)- [j8]Zhenyang Xu, Yongqiang Tian, Mengxiao Zhang, Jiarui Zhang, Puzhuo Liu, Yu Jiang, Chengnian Sun:
T-Rec: Fine-Grained Language-Agnostic Program Reduction Guided by Lexical Syntax. ACM Trans. Softw. Eng. Methodol. 34(2): 34:1-34:31 (2025) - 2024
- [j7]Yongqiang Tian, Xueyan Zhang, Yiwen Dong, Zhenyang Xu, Mengxiao Zhang, Yu Jiang, Shing-Chi Cheung, Chengnian Sun:
On the Caching Schemes to Speed Up Program Reduction. ACM Trans. Softw. Eng. Methodol. 33(1): 17:1-17:30 (2024) - 2023
- [j6]Zhenyang Xu, Yongqiang Tian, Mengxiao Zhang, Gaosen Zhao, Yu Jiang, Chengnian Sun:
Pushing the Limit of 1-Minimality of Language-Agnostic Program Reduction. Proc. ACM Program. Lang. 7(OOPSLA1): 636-664 (2023) - [j5]Yiwen Dong, Zheyang Li, Yongqiang Tian, Chengnian Sun, Michael W. Godfrey, Meiyappan Nagappan:
Bash in the Wild: Language Usage, Code Smells, and Bugs. ACM Trans. Softw. Eng. Methodol. 32(1): 8:1-8:22 (2023) - [j4]Meiziniu Li, Jialun Cao, Yongqiang Tian, Tsz On Li, Ming Wen, Shing-Chi Cheung:
COMET: Coverage-guided Model Generation For Deep Learning Library Testing. ACM Trans. Softw. Eng. Methodol. 32(5): 127:1-127:34 (2023) - [j3]Yongqiang Tian, Wuqi Zhang, Ming Wen, Shing-Chi Cheung, Chengnian Sun, Shiqing Ma, Yu Jiang:
Finding Deviated Behaviors of the Compressed DNN Models for Image Classifications. ACM Trans. Softw. Eng. Methodol. 32(5): 128:1-128:32 (2023) - 2021
- [j2]Yongqiang Tian, Shiqing Ma, Ming Wen, Yepang Liu, Shing-Chi Cheung, Xiangyu Zhang:
To what extent do DNN-based image classification models make unreliable inferences? Empir. Softw. Eng. 26(4): 84 (2021) - [j1]Ming Wen, Junjie Chen, Yongqiang Tian, Rongxin Wu, Dan Hao, Shi Han, Shing-Chi Cheung:
Historical Spectrum Based Fault Localization. IEEE Trans. Software Eng. 47(11): 2348-2368 (2021)
Conference and Workshop Papers
- 2025
- [c20]Xintong Zhou, Zhenyang Xu, Mengxiao Zhang, Yongqiang Tian, Chengnian Sun:
WDD: Weighted Delta Debugging. ICSE 2025: 1592-1603 - [c19]Mengxiao Zhang, Zhenyang Xu, Yongqiang Tian, Xinru Cheng, Chengnian Sun:
Toward a Better Understanding of Probabilistic Delta Debugging. ICSE 2025: 2024-2035 - [c18]Qingchao Shen, Yongqiang Tian, Haoyang Ma, Junjie Chen, Lili Huang, Ruifeng Fu, Shing-Chi Cheung, Zan Wang:
A Tale of Two DL Cities: When Library Tests Meet Compiler. ICSE 2025: 2201-2212 - [c17]Yuanmin Xie, Zhenyang Xu, Yongqiang Tian, Min Zhou, Xintong Zhou, Chengnian Sun:
Kitten: A Simple Yet Effective Baseline for Evaluating LLM-Based Compiler Testing Techniques. ISSTA Companion 2025: 21-25 - 2024
- [c16]Mengxiao Zhang, Yongqiang Tian, Zhenyang Xu, Yiwen Dong, Shin Hwei Tan, Chengnian Sun:
LPR: Large Language Models-Aided Program Reduction. ISSTA 2024: 261-273 - [c15]Haoyang Ma, Wuqi Zhang, Qingchao Shen, Yongqiang Tian, Junjie Chen, Shing-Chi Cheung:
Towards Understanding the Bugs in Solidity Compiler. ISSTA 2024: 1312-1324 - 2023
- [c14]Theodore Luo Wang, Yongqiang Tian, Yiwen Dong, Zhenyang Xu, Chengnian Sun:
Compilation Consistency Modulo Debug Information. ASPLOS (2) 2023: 146-158 - [c13]Yongqiang Tian, Zhenyang Xu, Yiwen Dong, Chengnian Sun, Shing-Chi Cheung:
Revisiting the Evaluation of Deep Learning-Based Compiler Testing. IJCAI 2023: 4873-4882 - [c12]Haoyang Ma, Qingchao Shen, Yongqiang Tian, Junjie Chen, Shing-Chi Cheung:
Fuzzing Deep Learning Compilers with HirGen. ISSTA 2023: 248-260 - [c11]Quan Zhang, Yongqiang Tian, Yifeng Ding, Shanshan Li, Chengnian Sun, Yu Jiang, Jiaguang Sun:
CoopHance: Cooperative Enhancement for Robustness of Deep Learning Systems. ISSTA 2023: 753-765 - [c10]Mengxiao Zhang, Zhenyang Xu, Yongqiang Tian, Yu Jiang, Chengnian Sun:
PPR: Pairwise Program Reduction. ESEC/SIGSOFT FSE 2023: 338-349 - [c9]Jia Le Tian, Mengxiao Zhang, Zhenyang Xu, Yongqiang Tian, Yiwen Dong, Chengnian Sun:
Ad Hoc Syntax-Guided Program Reduction. ESEC/SIGSOFT FSE 2023: 2137-2141 - 2022
- [c8]Jialun Cao, Meiziniu Li, Xiao Chen, Ming Wen, Yongqiang Tian, Bo Wu, Shing-Chi Cheung:
DeepFD: Automated Fault Diagnosis and Localization for Deep Learning Programs. ICSE 2022: 573-585 - [c7]Yiwen Dong, Tianxiao Gu, Yongqiang Tian, Chengnian Sun:
SnR: Constraint-Based Type Inference for Incomplete Java Code Snippets. ICSE 2022: 1982-1993 - 2021
- [c6]Quan Zhang, Yifeng Ding, Yongqiang Tian, Jianmin Guo, Min Yuan, Yu Jiang:
AdvDoor: adversarial backdoor attack of deep learning system. ISSTA 2021: 127-138 - [c5]Qingchao Shen, Haoyang Ma, Junjie Chen, Yongqiang Tian, Shing-Chi Cheung, Xiang Chen:
A comprehensive study of deep learning compiler bugs. ESEC/SIGSOFT FSE 2021: 968-980 - 2020
- [c4]Yongqiang Tian, Zhihua Zeng, Ming Wen, Yepang Liu, Tzu-yang Kuo, Shing-Chi Cheung:
EvalDNN: a toolbox for evaluating deep neural network models. ICSE (Companion Volume) 2020: 45-48 - 2019
- [c3]Ming Wen, Rongxin Wu, Yepang Liu, Yongqiang Tian, Xuan Xie, Shing-Chi Cheung, Zhendong Su:
Exploring and exploiting the correlations between bug-inducing and bug-fixing commits. ESEC/SIGSOFT FSE 2019: 326-337 - 2017
- [c2]Zhixiong Niu, Hong Xu, Libin Liu, Yongqiang Tian, Peng Wang, Zhenhua Li:
Unveiling performance of NFV software dataplanes. CAN@CoNEXT 2017: 13-18 - 2016
- [c1]Che Zhang, Hong Xu, Libin Liu, Zhixiong Niu, Peng Wang, Yongqiang Tian, Chengchen Hu:
Kuijia: Traffic rescaling in data center WANs. Sarnoff Symposium 2016: 142-147
Data and Artifacts
- 2023
- [d3]Zhenyang Xu, Yongqiang Tian, Mengxiao Zhang, Gaosen Zhao, Yu Jiang, Chengnian Sun:
Artifact for "Pushing the Limit of 1-Minimality of Language-Agnostic Program Reduction". Version 1. Zenodo, 2023 [all versions]
- [d2]Zhenyang Xu, Yongqiang Tian, Mengxiao Zhang, Gaosen Zhao, Yu Jiang, Chengnian Sun:
Artifact for "Pushing the Limit of 1-Minimality of Language-Agnostic Program Reduction". Version 2. Zenodo, 2023 [all versions] - [d1]Mengxiao Zhang, Zhenyang Xu, Yongqiang Tian, Yu Jiang, Chengnian Sun:
Artifact for "PPR: Pairwise Program Reduction". Zenodo, 2023
Informal and Other Publications
- 2025
- [i16]Yiwen Dong, Zhenyang Xu, Yongqiang Tian, Chengnian Sun:
Beyond Memorization: Evaluating the True Type Inference Capabilities of LLMs for Java Code Snippets. CoRR abs/2503.04076 (2025) - [i15]Haoyang Ma, Alastair F. Donaldson, Qingchao Shen, Yongqiang Tian, Junjie Chen, Shing-Chi Cheung:
Bounded Exhaustive Random Program Generation for Testing Solidity Compilers and Analyzers. CoRR abs/2503.20332 (2025) - [i14]Weiqi Lu, Yongqiang Tian, Xiaohan Zhong, Haoyang Ma, Zhenyang Xu, Shing-Chi Cheung, Chengnian Sun:
An Empirical Study of Bugs in Data Visualization Libraries. CoRR abs/2506.15084 (2025) - [i13]Zhenyang Xu, Hongxu Xu, Yongqiang Tian, Xintong Zhou, Chengnian Sun:
Leveraging Large Language Models to Detect Missed Peephole Optimizations. CoRR abs/2508.16125 (2025) - 2024
- [i12]Meiziniu Li, Dongze Li, Jianmeng Liu, Jialun Cao, Yongqiang Tian, Shing-Chi Cheung:
DLLens: Testing Deep Learning Libraries via LLM-aided Synthesis. CoRR abs/2406.07944 (2024) - [i11]Haoyang Ma, Wuqi Zhang, Qingchao Shen, Yongqiang Tian, Junjie Chen, Shing-Chi Cheung:
Towards Understanding the Bugs in Solidity Compiler. CoRR abs/2407.05981 (2024) - [i10]Qingchao Shen, Yongqiang Tian, Haoyang Ma, Junjie Chen, Lili Huang, Ruifeng Fu, Shing-Chi Cheung, Zan Wang:
A Tale of Two DL Cities: When Library Tests Meet Compiler. CoRR abs/2407.16626 (2024) - [i9]Mengxiao Zhang, Zhenyang Xu, Yongqiang Tian, Xinru Cheng, Chengnian Sun:
Deep Dive into Probabilistic Delta Debugging: Insights and Simplifications. CoRR abs/2408.04735 (2024) - [i8]Xintong Zhou, Zhenyang Xu, Mengxiao Zhang, Yongqiang Tian, Chengnian Sun:
WDD: Weighted Delta Debugging. CoRR abs/2411.19410 (2024) - 2023
- [i7]Mengxiao Zhang, Yongqiang Tian, Zhenyang Xu, Yiwen Dong, Shin Hwei Tan, Chengnian Sun:
Lampr: Boosting the Effectiveness of Language-Generic Program Reduction via Large Language Models. CoRR abs/2312.13064 (2023) - 2022
- [i6]Jialun Cao, Meiziniu Li, Xiao Chen, Ming Wen, Yongqiang Tian, Bo Wu, Shing-Chi Cheung:
DeepFD: Automated Fault Diagnosis and Localization for Deep Learning Programs. CoRR abs/2205.01938 (2022) - [i5]Meiziniu Li, Jialun Cao, Yongqiang Tian, Tsz On Li, Ming Wen, Shing-Chi Cheung:
MEMO: Coverage-guided Model Generation For Deep Learning Library Testing. CoRR abs/2208.01508 (2022) - [i4]Haoyang Ma, Qingchao Shen, Yongqiang Tian, Junjie Chen, Shing-Chi Cheung:
HirFuzz: Detecting High-Level Optimization Bugs in DL Compilers via Computational Graph Generation. CoRR abs/2208.02193 (2022) - 2021
- [i3]Yongqiang Tian, Wuqi Zhang, Ming Wen, Shing-Chi Cheung, Chengnian Sun, Shiqing Ma, Yu Jiang:
Fast Test Input Generation for Finding Deviated Behaviors in Compressed Deep Neural Network. CoRR abs/2112.02819 (2021) - 2019
- [i2]Yongqiang Tian, Shiqing Ma, Ming Wen, Yepang Liu, Shing-Chi Cheung, Xiangyu Zhang:
Testing Deep Learning Models for Image Analysis Using Object-Relevant Metamorphic Relations. CoRR abs/1909.03824 (2019) - 2016
- [i1]Zhixiong Niu, Hong Xu, Yongqiang Tian, Libin Liu, Peng Wang, Zhenhua Li:
Benchmarking NFV Software Dataplanes. CoRR abs/1605.05843 (2016)
Coauthor Index
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