Kuijia: Traffic rescaling in data center WANs. - Che Zhang; Hong Xu 001; Libin Liu 001; Zhixiong Niu; Peng Wang 037; Yongqiang Tian 001; Chengchen Hu (Sarnoff Symposium, 2016)

Benchmarking NFV Software Dataplanes. - Zhixiong Niu; Hong Xu 001; Yongqiang Tian 001; Libin Liu 001; Peng Wang 037; Zhenhua Li 001 (CoRR, 2016)

Unveiling performance of NFV software dataplanes. - Zhixiong Niu; Hong Xu 001; Libin Liu 001; Yongqiang Tian 001; Peng Wang 037; Zhenhua Li 001 (CAN@CoNEXT, 2017)

Exploring and exploiting the correlations between bug-inducing and bug-fixing commits. - Ming Wen 001; Rongxin Wu; Yepang Liu 001; Yongqiang Tian 001; Xuan Xie; Shing-Chi Cheung; Zhendong Su 001 (ESEC/SIGSOFT FSE, 2019)

Testing Deep Learning Models for Image Analysis Using Object-Relevant Metamorphic Relations. - Yongqiang Tian 001; Shiqing Ma; Ming Wen 001; Yepang Liu 001; Shing-Chi Cheung; Xiangyu Zhang 001 (CoRR, 2019)

EvalDNN: a toolbox for evaluating deep neural network models. - Yongqiang Tian 001; Zhihua Zeng; Ming Wen 001; Yepang Liu 001; Tzu-yang Kuo; Shing-Chi Cheung (ICSE (Companion Volume), 2020)

AdvDoor: adversarial backdoor attack of deep learning system. - Quan Zhang; Yifeng Ding; Yongqiang Tian 001; Jianmin Guo; Min Yuan; Yu Jiang 001 (ISSTA, 2021)

A comprehensive study of deep learning compiler bugs. - Qingchao Shen; Haoyang Ma; Junjie Chen 003; Yongqiang Tian 001; Shing-Chi Cheung; Xiang Chen 005 (ESEC/SIGSOFT FSE, 2021)

Fast Test Input Generation for Finding Deviated Behaviors in Compressed Deep Neural Network. - Yongqiang Tian 001; Wuqi Zhang; Ming Wen 001; Shing-Chi Cheung; Chengnian Sun; Shiqing Ma; Yu Jiang 001 (CoRR, 2021)

To what extent do DNN-based image classification models make unreliable inferences? - Yongqiang Tian 001; Shiqing Ma; Ming Wen 001; Yepang Liu 001; Shing-Chi Cheung; Xiangyu Zhang 001 (Empir. Softw. Eng., 2021)

Historical Spectrum Based Fault Localization. - Ming Wen 001; Junjie Chen 003; Yongqiang Tian 001; Rongxin Wu; Dan Hao 001; Shi Han; Shing-Chi Cheung (IEEE Trans. Software Eng., 2021)

DeepFD: Automated Fault Diagnosis and Localization for Deep Learning Programs. - Jialun Cao; Meiziniu Li; Xiao Chen; Ming Wen 001; Yongqiang Tian 001; Bo Wu 018; Shing-Chi Cheung (ICSE, 2022)

SnR: Constraint-Based Type Inference for Incomplete Java Code Snippets. - Yiwen Dong 002; Tianxiao Gu; Yongqiang Tian 001; Chengnian Sun (ICSE, 2022)

MEMO: Coverage-guided Model Generation For Deep Learning Library Testing. - Meiziniu Li; Jialun Cao; Yongqiang Tian 001; Tsz On Li; Ming Wen 001; Shing-Chi Cheung (CoRR, 2022)

HirFuzz: Detecting High-Level Optimization Bugs in DL Compilers via Computational Graph Generation. - Haoyang Ma; Qingchao Shen; Yongqiang Tian 001; Junjie Chen 003; Shing-Chi Cheung (CoRR, 2022)

Compilation Consistency Modulo Debug Information. - Theodore Luo Wang; Yongqiang Tian 001; Yiwen Dong 002; Zhenyang Xu; Chengnian Sun (ASPLOS (2), 2023)

Revisiting the Evaluation of Deep Learning-Based Compiler Testing. - Yongqiang Tian 001; Zhenyang Xu; Yiwen Dong 002; Chengnian Sun; Shing-Chi Cheung (IJCAI, 2023)

Fuzzing Deep Learning Compilers with HirGen. - Haoyang Ma; Qingchao Shen; Yongqiang Tian 001; Junjie Chen 003; Shing-Chi Cheung (ISSTA, 2023)

CoopHance: Cooperative Enhancement for Robustness of Deep Learning Systems. - Quan Zhang; Yongqiang Tian 001; Yifeng Ding; Shanshan Li 001; Chengnian Sun; Yu Jiang 001; Jiaguang Sun 001 (ISSTA, 2023)

Ad Hoc Syntax-Guided Program Reduction. - Jia Le Tian; Mengxiao Zhang; Zhenyang Xu; Yongqiang Tian 001; Yiwen Dong 002; Chengnian Sun (ESEC/SIGSOFT FSE, 2023)

PPR: Pairwise Program Reduction. - Mengxiao Zhang; Zhenyang Xu; Yongqiang Tian 001; Yu Jiang 001; Chengnian Sun (ESEC/SIGSOFT FSE, 2023)

Lampr: Boosting the Effectiveness of Language-Generic Program Reduction via Large Language Models. - Mengxiao Zhang; Yongqiang Tian 001; Zhenyang Xu; Yiwen Dong 002; Shin Hwei Tan; Chengnian Sun (CoRR, 2023)

Bash in the Wild: Language Usage, Code Smells, and Bugs. - Yiwen Dong 002; Zheyang Li; Yongqiang Tian 001; Chengnian Sun; Michael W. Godfrey; Meiyappan Nagappan (ACM Trans. Softw. Eng. Methodol., 2023)

Pushing the Limit of 1-Minimality of Language-Agnostic Program Reduction. - Zhenyang Xu; Yongqiang Tian 001; Mengxiao Zhang; Gaosen Zhao; Yu Jiang 001; Chengnian Sun (Proc. ACM Program. Lang., 2023)

Artifact for "Pushing the Limit of 1-Minimality of Language-Agnostic Program Reduction". - Zhenyang Xu; Yongqiang Tian 001; Mengxiao Zhang; Gaosen Zhao; Yu Jiang 001; Chengnian Sun (Zenodo, 2023)

Artifact for "Pushing the Limit of 1-Minimality of Language-Agnostic Program Reduction". - Zhenyang Xu; Yongqiang Tian 001; Mengxiao Zhang; Gaosen Zhao; Yu Jiang 001; Chengnian Sun (Zenodo, 2023)

Artifact for "PPR: Pairwise Program Reduction". - Mengxiao Zhang; Zhenyang Xu; Yongqiang Tian 001; Yu Jiang 001; Chengnian Sun (Zenodo, 2023)

COMET: Coverage-guided Model Generation For Deep Learning Library Testing. - Meiziniu Li; Jialun Cao; Yongqiang Tian 001; Tsz On Li; Ming Wen 001; Shing-Chi Cheung (ACM Trans. Softw. Eng. Methodol., 2023)

Finding Deviated Behaviors of the Compressed DNN Models for Image Classifications. - Yongqiang Tian 001; Wuqi Zhang; Ming Wen 001; Shing-Chi Cheung; Chengnian Sun; Shiqing Ma; Yu Jiang 001 (ACM Trans. Softw. Eng. Methodol., 2023)

Towards Understanding the Bugs in Solidity Compiler. - Haoyang Ma; Wuqi Zhang; Qingchao Shen; Yongqiang Tian 001; Junjie Chen 003; Shing-Chi Cheung (ISSTA, 2024)

LPR: Large Language Models-Aided Program Reduction. - Mengxiao Zhang; Yongqiang Tian 001; Zhenyang Xu; Yiwen Dong 002; Shin Hwei Tan; Chengnian Sun (ISSTA, 2024)

DLLens: Testing Deep Learning Libraries via LLM-aided Synthesis. - Meiziniu Li; Dongze Li; Jianmeng Liu; Jialun Cao; Yongqiang Tian 001; Shing-Chi Cheung (CoRR, 2024)

Deep Dive into Probabilistic Delta Debugging: Insights and Simplifications. - Mengxiao Zhang; Zhenyang Xu; Yongqiang Tian 001; Xinru Cheng; Chengnian Sun (CoRR, 2024)

On the Caching Schemes to Speed Up Program Reduction. - Yongqiang Tian 001; Xueyan Zhang; Yiwen Dong 002; Zhenyang Xu; Mengxiao Zhang; Yu Jiang 001; Shing-Chi Cheung; Chengnian Sun (ACM Trans. Softw. Eng. Methodol., 2024)

A Tale of Two DL Cities: When Library Tests Meet Compiler. - Qingchao Shen; Yongqiang Tian 001; Haoyang Ma; Junjie Chen 003; Lili Huang; Ruifeng Fu; Shing-Chi Cheung; Zan Wang (ICSE, 2025)

Toward a Better Understanding of Probabilistic Delta Debugging. - Mengxiao Zhang; Zhenyang Xu; Yongqiang Tian 001; Xinru Cheng; Chengnian Sun (ICSE, 2025)

WDD: Weighted Delta Debugging. - Xintong Zhou; Zhenyang Xu; Mengxiao Zhang; Yongqiang Tian 001; Chengnian Sun (ICSE, 2025)

Kitten: A Simple Yet Effective Baseline for Evaluating LLM-Based Compiler Testing Techniques. - Yuanmin Xie; Zhenyang Xu; Yongqiang Tian 001; Min Zhou 001; Xintong Zhou; Chengnian Sun (ISSTA Companion, 2025)

An Empirical Study of Bugs in Data Visualization Libraries. - Weiqi Lu; Yongqiang Tian 001; Xiaohan Zhong; Haoyang Ma; Zhenyang Xu; Shing-Chi Cheung; Chengnian Sun (Proc. ACM Softw. Eng., 2025)

T-Rec: Fine-Grained Language-Agnostic Program Reduction Guided by Lexical Syntax. - Zhenyang Xu; Yongqiang Tian 001; Mengxiao Zhang; Jiarui Zhang; Puzhuo Liu; Yu Jiang 001; Chengnian Sun (ACM Trans. Softw. Eng. Methodol., 2025)

Beyond Memorization: Evaluating the True Type Inference Capabilities of LLMs for Java Code Snippets. - Yiwen Dong 002; Zhenyang Xu; Yongqiang Tian 001; Chengnian Sun (CoRR, 2025)

Bounded Exhaustive Random Program Generation for Testing Solidity Compilers and Analyzers. - Haoyang Ma; Alastair F. Donaldson; Qingchao Shen; Yongqiang Tian 001; Junjie Chen 003; Shing-Chi Cheung (CoRR, 2025)