Towards Concolic Testing for Hybrid Systems. - Pingfan Kong; Yi Li 010; Xiaohong Chen 002; Jun Sun 001; Meng Sun 002; Jingyi Wang 004 (FM, 2016)

Service Adaptation with Probabilistic Partial Models. - Manman Chen; Tian Huat Tan; Jun Sun 001; Jingyi Wang 004; Yang Liu 003; Jing Sun 002; Jin Song Dong (ICFEM, 2016)

Verifying Complex Systems Probabilistically through Learning, Abstraction and Refinement. - Jingyi Wang 004; Jun Sun 001; Shengchao Qin (CoRR, 2016)

Should We Learn Probabilistic Models for Model Checking? A New Approach and An Empirical Study. - Jingyi Wang 004; Jun Sun 001; Qixia Yuan; Jun Pang 001 (FASE, 2017)

Learning Likely Invariants to Explain Why a Program Fails. - Long H. Pham; Jun Sun 001; Lyly Tran Thi; Jingyi Wang 004; Xin Peng 001 (ICECCS, 2017)

Improving Probability Estimation Through Active Probabilistic Model Learning. - Jingyi Wang 004; Xiaohong Chen 002; Jun Sun 001; Shengchao Qin (ICFEM, 2017)

Toward 'verifying' a Water Treatment System. - Jingyi Wang 004; Jun Sun 001; Yifan Jia 002 (CoRR, 2017)

Importance Sampling of Interval Markov Chains. - Cyrille Jégourel; Jingyi Wang 004; Jun Sun 001 (DSN, 2018)

Towards 'Verifying' a Water Treatment System. - Jingyi Wang 004; Jun Sun 001; Yifan Jia 002; Shengchao Qin; Zhiwu Xu 001 (FM, 2018)

Towards optimal concolic testing. - Xinyu Wang 001; Jun Sun 001; Zhenbang Chen; Peixin Zhang 001; Jingyi Wang 004; Yun Lin 001 (ICSE, 2018)

Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing. - Jingyi Wang 004; Jun Sun 001; Peixin Zhang 001; Xinyu Wang 001 (CoRR, 2018)

Learning probabilistic models for model checking: an evolutionary approach and an empirical study. - Jingyi Wang 004; Jun Sun 001; Qixia Yuan; Jun Pang 001 (Int. J. Softw. Tools Technol. Transf., 2018)

Adversarial sample detection for deep neural network through model mutation testing. - Jingyi Wang 004; Guoliang Dong; Jun Sun 001; Xinyu Wang 001; Peixin Zhang 001 (ICSE, 2019)

Analyzing Recurrent Neural Network by Probabilistic Abstraction. - Guoliang Dong; Jingyi Wang 004; Jun Sun 001; Yang Zhang; Xinyu Wang 001; Ting Dai; Jin Song Dong (CoRR, 2019)

There is Limited Correlation between Coverage and Robustness for Deep Neural Networks. - Yizhen Dong; Peixin Zhang 001; Jingyi Wang 004; Shuang Liu 007; Jun Sun 001; Jianye Hao; Xinyu Wang 001; Li Wang; Jin Song Dong; Dai Ting (CoRR, 2019)

An Empirical Study on Correlation between Coverage and Robustness for Deep Neural Networks. - Yizhen Dong; Peixin Zhang 001; Jingyi Wang 004; Shuang Liu 007; Jun Sun 001; Jianye Hao; Xinyu Wang 001; Li Wang; Jin Song Dong; Ting Dai (ICECCS, 2020)

White-box fairness testing through adversarial sampling. - Peixin Zhang 001; Jingyi Wang 004; Jun Sun 001; Guoliang Dong; Xinyu Wang 001; Xingen Wang; Jin Song Dong 001; Ting Dai (ICSE, 2020)

Towards Interpreting Recurrent Neural Networks through Probabilistic Abstraction. - Guoliang Dong; Jingyi Wang 004; Jun Sun 001; Yang Zhang; Xinyu Wang 001; Ting Dai; Jin Song Dong; Xingen Wang (ASE, 2020)

Towards Repairing Neural Networks Correctly. - Guoliang Dong; Jun Sun 001; Jingyi Wang 004; Xinyu Wang 001; Ting Dai (CoRR, 2020)

RobOT: Robustness-Oriented Testing for Deep Learning Systems. - Jingyi Wang 004; Jialuo Chen; Youcheng Sun; Xingjun Ma; Dongxia Wang 002; Jun Sun 001; Peng Cheng 001 (ICSE, 2021)

Attack as defense: characterizing adversarial examples using robustness. - Zhe Zhao 007; Guangke Chen; Jingyi Wang 004; Yiwei Yang 002; Fu Song; Jun Sun 001 (ISSTA, 2021)

Improving Neural Network Verification through Spurious Region Guided Refinement. - Pengfei Yang 002; Renjue Li; Jianlin Li; Cheng-Chao Huang; Jingyi Wang 004; Jun Sun 001; Bai Xue 001; Lijun Zhang 001 (TACAS (1), 2021)

Automatic Fairness Testing of Neural Classifiers through Adversarial Sampling. - Peixin Zhang 001; Jingyi Wang 004; Jun Sun 001; Xinyu Wang 001; Guoliang Dong; Xingen Wang; Ting Dai; Jin Song Dong (CoRR, 2021)

Fairness Testing of Deep Image Classification with Adequacy Metrics. - Peixin Zhang 001; Jingyi Wang 004; Jun Sun 001; Xinyu Wang 001 (CoRR, 2021)

Better Pay Attention Whilst Fuzzing. - Shunkai Zhu; Jingyi Wang 004; Jun Sun 001; Jie Yang 039; Xingwei Lin; Liyi Zhang; Peng Cheng 001 (CoRR, 2021)

Adversarial attacks and mitigation for anomaly detectors of cyber-physical systems. - Yifan Jia 002; Jingyi Wang 004; Christopher M. Poskitt; Sudipta Chattopadhyay 001; Jun Sun 001; Yuqi Chen 001 (Int. J. Crit. Infrastructure Prot., 2021)

Automatically 'Verifying' Discrete-Time Complex Systems through Learning, Abstraction and Refinement. - Jingyi Wang 004; Jun Sun 001; Shengchao Qin; Cyrille Jégourel (IEEE Trans. Software Eng., 2021)

NeuronFair: Interpretable White-Box Fairness Testing through Biased Neuron Identification. - Haibin Zheng; Zhiqing Chen; Tianyu Du; Xuhong Zhang 002; Yao Cheng; Shouling Ji; Jingyi Wang 004; Yue Yu 001; Jinyin Chen (ICSE, 2022)

Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models. - Jialuo Chen; Jingyi Wang 004; Tinglan Peng; Youcheng Sun; Peng Cheng 001; Shouling Ji; Xingjun Ma; Bo Li 026; Dawn Song (SP, 2022)

Repairing Adversarial Texts Through Perturbation. - Guoliang Dong; Jingyi Wang 004; Jun Sun 001; Sudipta Chattopadhyay 001; Xinyu Wang 001; Ting Dai; Jie Shi; Jin Song Dong (TASE, 2022)

Which neural network makes more explainable decisions? An approach towards measuring explainability. - Mengdi Zhang 003; Jun Sun 001; Jingyi Wang 004 (Autom. Softw. Eng., 2022)

K-ST: A Formal Executable Semantics of PLC Structured Text Language. - Kun Wang 023; Jingyi Wang 004; Christopher M. Poskitt; Xiangxiang Chen 002; Jun Sun 001; Peng Cheng 001 (CoRR, 2022)

Towards Comprehensively Understanding the Run-time Security of Programmable Logic Controllers: A 3-year Empirical Study. - Rongkuan Ma; Qiang Wei; Jingyi Wang 004; Shunkai Zhu; Shouling Ji; Peng Cheng 001; Yan Jia; Qingxian Wang (CoRR, 2022)

Automatic Fairness Testing of Neural Classifiers Through Adversarial Sampling. - Peixin Zhang 001; Jingyi Wang 004; Jun Sun 001; Xinyu Wang 001; Guoliang Dong; Xingen Wang; Ting Dai; Jin Song Dong 001 (IEEE Trans. Software Eng., 2022)

HODOR: Shrinking Attack Surface on Node.js via System Call Limitation. - Wenya Wang 003; Xingwei Lin; Jingyi Wang 004; Wang Gao; Dawu Gu; Wei Lv; Jiashui Wang (CCS, 2023)

Black-Box Fairness Testing with Shadow Models. - Weipeng Jiang; Chao Shen 001; Chenhao Lin; Jingyi Wang 004; Jun Sun 001; Xuanqi Gao (ICICS, 2023)

DEEPJUDGE: A Testing Framework for Copyright Protection of Deep Learning Models. - Jialuo Chen; Youcheng Sun; Jingyi Wang 004; Peng Cheng 001; Xingjun Ma (ICSE Companion, 2023)

FairRec: Fairness Testing for Deep Recommender Systems. - Huizhong Guo; Jinfeng Li; Jingyi Wang 004; Xiangyu Liu; Dongxia Wang 002; Zehong Hu; Rong Zhang 006; Hui Xue 001 (ISSTA, 2023)

Prompting Frameworks for Large Language Models: A Survey. - Xiaoxia Liu; Jingyi Wang 004; Jun Sun 001; Xiaohan Yuan; Guoliang Dong; Peng Di; Wenhai Wang; Dongxia Wang 002 (CoRR, 2023)

Defending Cyber-Physical Systems Through Reverse-Engineering-Based Memory Sanity Check. - Yangyang Geng; Yuqi Chen 001; Rongkuan Ma; Qiang Wei; Jie Pan; Jingyi Wang 004; Peng Cheng 001; Qingxian Wang (IEEE Internet Things J., 2023)

QuoTe: Quality-oriented Testing for Deep Learning Systems. - Jialuo Chen; Jingyi Wang 004; Xingjun Ma; Youcheng Sun; Jun Sun 001; Peixin Zhang 001; Peng Cheng 001 (ACM Trans. Softw. Eng. Methodol., 2023)

K-ST: A Formal Executable Semantics of the Structured Text Language for PLCs. - Kun Wang 023; Jingyi Wang 004; Christopher M. Poskitt; Xiangxiang Chen 002; Jun Sun 001; Peng Cheng 001 (IEEE Trans. Software Eng., 2023)

TestSGD: Interpretable Testing of Neural Networks against Subtle Group Discrimination. - Mengdi Zhang 003; Jun Sun 001; Jingyi Wang 004; Bing Sun (ACM Trans. Softw. Eng. Methodol., 2023)

Boosting Adversarial Training in Safety-Critical Systems Through Boundary Data Selection. - Yifan Jia 002; Christopher M. Poskitt; Peixin Zhang 001; Jingyi Wang 004; Jun Sun 001; Sudipta Chattopadhyay 001 (IEEE Robotics Autom. Lett., 2023)

K-RAPID: A Formal Executable Semantics of the RAPID Robot Programming Language. - Zichen Wang; Jingyi Wang 004; Fu Song; Kun Wang 023; Hongyi Pu; Peng Cheng 001 (CPSS@AsiaCCS, 2024)

VeRe: Verification Guided Synthesis for Repairing Deep Neural Networks. - Jianan Ma; Pengfei Yang 002; Jingyi Wang 004; Youcheng Sun; Cheng-Chao Huang; Zhen Wang 013 (ICSE, 2024)

Isolation-Based Debugging for Neural Networks. - Jialuo Chen; Jingyi Wang 004; Youcheng Sun; Peng Cheng 001; Jiming Chen 001 (ISSTA, 2024)

Interpretability Based Neural Network Repair. - Zuohui Chen; Jun Zhou; Youcheng Sun; Jingyi Wang 004; Qi Xuan 001; Xiaoniu Yang (ISSTA, 2024)

TeDA: A Testing Framework for Data Usage Auditing in Deep Learning Model Development. - Xiangshan Gao; Jialuo Chen; Jingyi Wang 004; Jie Shi; Peng Cheng 001; Jiming Chen 001 (ISSTA, 2024)

FAST: Boosting Uncertainty-based Test Prioritization Methods for Neural Networks via Feature Selection. - Jialuo Chen; Jingyi Wang 004; Xiyue Zhang 001; Youcheng Sun; Marta Kwiatkowska; Jiming Chen 001; Peng Cheng 001 (ASE, 2024)

S-Eval: Automatic and Adaptive Test Generation for Benchmarking Safety Evaluation of Large Language Models. - Xiaohan Yuan; Jinfeng Li; Dongxia Wang 002; Yuefeng Chen; Xiaofeng Mao; Longtao Huang; Hui Xue 001; Wenhai Wang; Kui Ren 001; Jingyi Wang 004 (CoRR, 2024)

Towards Real World Debiasing: A Fine-grained Analysis On Spurious Correlation. - Zhibo Wang 001; Peng Kuang; Zhixuan Chu; Jingyi Wang 004; Kui Ren 001 (CoRR, 2024)

Protecting Deep Learning Model Copyrights with Adversarial Example-Free Reuse Detection. - Xiaokun Luan; Xiyue Zhang 001; Jingyi Wang 004; Meng Sun 002 (CoRR, 2024)

μDrive: User-Controlled Autonomous Driving. - Kun Wang 023; Christopher M. Poskitt; Yang Sun 008; Jun Sun 001; Jingyi Wang 004; Peng Cheng 001; Jiming Chen 001 (CoRR, 2024)

RedTest: Towards Measuring Redundancy in Deep Neural Networks Effectively. - Yao Lu; Peixin Zhang 001; Jingyi Wang 004; Lei Ma; Xiaoniu Yang; Qi Xuan 001 (CoRR, 2024)

VeriFi: Towards Verifiable Federated Unlearning. - Xiangshan Gao; Xingjun Ma; Jingyi Wang 004; Youcheng Sun; Bo Li 026; Shouling Ji; Peng Cheng 001; Jiming Chen 001 (IEEE Trans. Dependable Secur. Comput., 2024)

Better Pay Attention Whilst Fuzzing. - Shunkai Zhu; Jingyi Wang 004; Jun Sun 001; Jie Yang 039; Xingwei Lin; Tian Wang 001; Liyi Zhang; Peng Cheng 001 (IEEE Trans. Software Eng., 2024)

Attack as Detection: Using Adversarial Attack Methods to Detect Abnormal Examples. - Zhe Zhao 007; Guangke Chen; Tong Liu; Taishan Li; Fu Song; Jingyi Wang 004; Jun Sun 001 (ACM Trans. Softw. Eng. Methodol., 2024)

Patch Synthesis for Property Repair of Deep Neural Networks. - Zhiming Chi; Jianan Ma; Pengfei Yang 002; Cheng-Chao Huang; Renjue Li; Jingyi Wang 004; Xiaowei Huang 001; Lijun Zhang 001 (ICSE, 2025)

LLM-Aided Automatic Modeling for Security Protocol Verification. - Ziyu Mao; Jingyi Wang 004; Jun Sun 001; Shengchao Qin; Jiawen Xiong (ICSE, 2025)

Quantitative Runtime Monitoring of Ethereum Transaction Attacks. - Xinyao Xu; Ziyu Mao; Jianzhong Su; Xingwei Lin; David Basin; Jun Sun 001; Jingyi Wang 004 (WWW, 2025)

S-Eval: Towards Automated and Comprehensive Safety Evaluation for Large Language Models. - Xiaohan Yuan; Jinfeng Li; Dongxia Wang 002; Yuefeng Chen; Xiaofeng Mao; Longtao Huang; Jialuo Chen; Hui Xue 001; Xiaoxia Liu; Wenhai Wang; Kui Ren 001; Jingyi Wang 004 (Proc. ACM Softw. Eng., 2025)

Efficient Function Orchestration for Large Language Models. - Xiaoxia Liu; Peng Di; Cong Li; Jun Sun 001; Jingyi Wang 004 (CoRR, 2025)

PRUNE: A Patching Based Repair Framework for Certifiable Unlearning of Neural Networks. - Xuran Li; Jingyi Wang 004; Xiaohan Yuan; Peixin Zhang 001; Zhan Qin; Zhibo Wang 001; Kui Ren 001 (CoRR, 2025)

Scuzer: A Scheduling Optimization Fuzzer for TVM. - Xiangxiang Chen 002; Xingwei Lin; Jingyi Wang 004; Jun Sun 001; Jiashui Wang; Wenhai Wang (ACM Trans. Softw. Eng. Methodol., 2025)

OptSE: Toward Optimal Symbolic Execution. - Shunkai Zhu; Jun Sun 001; Jingyi Wang 004; Xingwei Lin; Peng Cheng 001 (IEEE Trans. Software Eng., 2025)