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Publications

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Upcoming

  • Wei Zhao, Zhe Li, Yige Li, and Jun Sun: “Adversarial Suffixes May Be Features Too!”, arxiv
  • Zhe Li, Wei Zhao, Yige Li, and Jun Sun: “Do Influence Functions Work on Large Language Models?”, arxiv
  • Mengdi Zhang, Kai Kiat Goh, Peixin Zhang, and Jun Sun: “LLMScan: Causal Scan for LLM Misbehavior Detection”, arxiv

2025

  • Shuang Liu, Chenglin Tian, Jun Sun, Ruifeng Wang, Wei Lu, Yongxin Zhao, Yinxing Xue, Junjie Wang, and Xiaoyong Du: Semantic Conformance Testing of Relational DBMS, VLDB 2025. 
  • Yufan Cai, Zhe Hou, David Sanan, Xiaokun Luan, Yun Lin, Jun Sun, Jin Song Dong: Automated Program Refinement: Guide and Verify Code Large Language Model with Refinement Calculus, POPL 2025. 

2024

  • Wei Zhao, Zhe Li, Yige Li, Ye Zhang, and Jun Sun: Defending Large Language Models Against Jailbreak Attacks via Layer-specific Editing, Findings of EMNLP 2024. 
  • Yihao Zhang, Zeming Wei, Jun Sun and Meng Sun: Towards General Conceptual Model Editing via Adversarial Representation Engineering, NeurIPS 2024.
  • Jingnan Zheng, Han Wang, Tai D. Nguyen, An Zhang, Jun Sun, and Tat-Seng Chua: ALI-Agent: Assessing LLMs’Alignment with Human Values via Agent-based Evaluation, NeurIPS 2024. 
  • Ruihan Zhang, and Jun Sun: Certified Robust Accuracy of Neural Networks Are Bounded due to Bayes Errors, CAV 2024.
  • Yang Sun, Chris Poskitt, Xiaodong Zhang, and Jun Sun: REDriver: Runtime Enforcement for Autonomous Vehicles, ICSE 2024.
  • Ziqi Shuai, Zhenbang Chen, Kelin Ma, Kunlin Liu, Yufeng Zhang, Jun Sun, and Ji Wang: Partial Solution Based Constraint Solving Cache in Symbolic Execution, FSE 2024.
  • Jinhao Dong, Jun Sun, Yun Lin, Yedi Zhang, Murong Ma, Jin Song Dong, and Dan Hao: Revisting the Conflict-Resolving Problem from a Semantic Perspective, ASE 2024. 
  • Pham Hong Long, and Jun Sun: Certified Continual Learning for Neural Network Regression, ISSTA 2024.
  • Huijia Sun, Christopher M. Poskitt, Yang Sun, Jun Sun, and Yuqi Chen: ACAV: A Framework for Automatic Causality Analysis in Autonomous Vehicle Accident Recordings, ICSE 2024.
  • Bing Sun, Jun Sun, Wayne Koh, and Jie Shi: Neural Network Semantic Backdoor Detection and Mitigation: A Causality-Based Approach, USENIX Security 2024.
  • Yedi Zhang, Guangke Chen, Fu Song, Jun Sun and Jin Song Dong: Certified Quantization Strategy Synthesis for Neural Networks, Formal Methods 2024.
  • Shunkai Zhu, Jingyi Wang, Jun Sun, Jie Yang, Xingwei Lin, Liyi Zhang, and Peng Cheng: Better Pay Attention Whilst Fuzzing, IEEE Transactions on Software Engineering, 2024.
  • Zhe Zhao, Guangke Chen, Tong Liu, Taishan Li, Fu Song, Jingyi Wang, and Jun Sun: Attack as Detection: Using Adversarial Attack Methods to Detect Abnormal Examples, ACM Transactions on Software Engineering Methodology, 2024.
  • Yinxing Xue, Jiaming Ye, Wei Zhang, Jun Sun, Lei Ma, Haijun Wang, Jianjun Zhao: xFuzz: Machine Learning Guided Cross-Contract Fuzzing, IEEE Trans. Dependable Secur. Comput. 21(2): 515-529 (2024)
  • Yuhan Zhi, Xiaofei Xie, Chao Shen, Jun Sun, Xiaoyu Zhang, and Xiaohong Guan: Seed Selection for Testing Deep Neural Networks, ACM Transactions on Software Engineering Methodology, 2024.
  • Dongxia Wang, Tim Muller, Jun Sun: Provably Secure Decisions based on Potentially Malicious Information, IEEE Transactions on Dependable and Secure Computing, 2024.
2023
  • Yedi Zhang, Fu Song, and Jun Sun: QEBVerif: Quantization Error Bound Verification of Neural Networks, CAV 2023.
  • Bozhi Wu, Shangqing Liu, Yang Xiao, Zhiming Li, Jun Sun, and Shang-Wei Lin: Learning Program Semantics for Vulnerability Detection via Vulnerability-specific Inter-procedural Slicing, FSE 2023.
  • Lida Zhao, Sen Chen, Zhengzi Xu, Lyuye Zhang, Jiahui Wu, Jun Sun and Yang Liu: Software Composition Analysis for Vulnerability Detection: An Empirical Study on Java Projects, FSE 2023. 
  • Mengdi Zhang, Jun Sun, Jingyi Wang, and Bing Sun: Interpretable Testing of Neural Networks Against Subtle Group Discrimination, ACM Transactions on Software Engineering Methodology, 2023.
  • Yuan Zhou, Yang Sun, Yun Tang, Yuqi Chen, and Jun Sun: Specification-based Autonomous Driving System Testing, IEEE Transactions on Software Engineering, 2023. 
  • Richard Schumi, and Jun Sun: Semantic-based Neural Network Repair, ISSTA 2023.
  • Kun Wang, Jingyi Wang, Chris Poskitt, Xiangxiang Chen, Jun Sun and Peng Cheng: K-ST: A Formal Executable Semantics of the Structured Text Languages for PLCs, TSE 2023.
  • Bohan Xuan, Fan Zhang, Mei Qian, Yuqi Chen, Wei Lin, Chris Poskitt, Jun Sun, and Binbin Chen: Constructing Cyber-Physical System Testing Suites using Active Sensor Fuzzing, IEEE Transactions on Software Engineering, 2023.
  • Chen Yang, Junjie Chen, Xingyu Fan, Jiajun Jiang, and Jun Sun: Silent Compiler Bug De-duplication via Three-Dimensional Analysis, ISSTA 2023. 
  • Xiaodong Zhang, Zhao Wei, Yang Sun, Jun Sun, Yulong Shen, Xuewen Dong, and Zijiang Yang: Testing Automated Driving Systems by Breaking Many Laws Efficiently, ISSTA 2023.
  • Christopher M. Poskitt, Yuqi Chen, Jun Sun, and Yu Jiang: Finding Causally Different Tests for a Cyber-Physical System, ICSE 2023.
  • Xiaoning Ren, Yun Lin, Yinxing Xue, Ruofan Liu, Jun Sun, Zhiyong Feng, and Jinsong Dong: DeepArc: Modularizing Neural Networks for the Model Maintenance, ICSE 2023.
  • Shuzheng Gao, Cuiyun Gao, Chaozheng Wang, Jun Sun, David Lo, and Yue Yu: Two Sides of the Same Coin: Exploiting the Impact of Identifiers in Neural Code Comprehension, ICSE 2023.
  • Jialuo Chen, Jingyi Wang, Xingjun Ma, Youcheng Sun, Jun Sun, Peixin Zhang, and Peng Cheng. QuoTe: Quality-oriented Testing for Deep Learning Systems, ACM Transactions on Software Engineering Methodology, 2023.
  • Andre Etienne, Shuang Liu, Yang Liu, Christine Choppy, Jun Sun, and Jinsong Dong: Formalizing UML State Machines for Automated Verification — A Survey, ACM Computing Surveys, 2023. 
  • Yifan Jia, Christopher M. Poskitt, Peixin Zhang, Jingyi Wang*, Jun Sun, and Sudipta Chattopadhyay: Boosting Adversarial Training in Safety-Critical Systems through Boundary Data Selection. IEEE Robotics and Automation Letters 2023.
  • Mingtian Tan, Xiaofei Xie, Jun Sun, Tianhao Wang: Mitigating Membership Inference Attacks via Weighted Smoothing. ACSAC 2023: 787-798
  • Feng Zhang, Leping Zhang, Yongwang Zhao, Yang Liu, Jun Sun: Refinement-based Specification and Analysis of Multi-core ARINC 653 Using Event-B, Formal Aspects Comput. 35(4): 24:1-24:29 (2023)
2022
  • Pham Hong Long, and Jun Sun: Verifying Neural Networks Against Backdoor Attacks, CAV 2022.
  • Xuan Bach Le, Shang-Wei Lin, Jun Sun, and David Sanan: Quantum Separation Logic: A Framework for Local Reasoning of Quantum Programs, POPL 2022.
  • Mengdi Zhang, and Jun Sun: Adaptive Fairness Improvement based Causality Analysis, ESEC/FSE 2022.
  • Bing Sun, Jun Sun, Pham Hong Long and Jie Shi: Causality-based Neural Network Repair, ICSE 2022.
  • Richard Schumi, and Jun Sun: ExAIs: Executable AI Semantics, ICSE 2022.
  • Yang Sun, Chris Poskitt, Jun Sun, Yuqi Chen and Zijiang Yang: LawBreaker: An Approach for Specifying Traffic Laws and Fuzzing Autonomous Vehicles, ASE 2022.
  • Yedi Zhang, Zhe Zhao, Guangke Chen, Fu Song, Min Zhang, Taolue Chen, and Jun Sun: QVIP: An ILP-based Formal Verification Approach for Quantized Neural Networks, ASE 2022.
  • Étienne André, Didier Lime, Dylan Marinho and Jun Sun: Guaranteeing Timed Opacity using Parametric Timed Model Checking, ACM Transactions on Software Engineering Methodology, 2022.
  • Yingquan Zhao, Zan Wang, Shuang Liu, Jun Sun, Junjie Chen, Xiang Chen: Achieving High MAP-Coverage through Pattern Constraint Reduction, IEEE Transactions on Software Engineering, 2022.
  • Mengdi Zhang, Jun Sun and Jingyi Wang: Which neural network makes more explainable decisions? An approach towards measuring explainability, ASE Journal, 2022.
  • Chi Chen, Xin Peng, Bihuan Chen, Jun Sun, Zhenchang Xing, Xin Wang, Wenyun Zhao: More Than Deep Learning: Post-processing for API Sequence Recommendation, Empir. Softw. Eng. 27(1): 15 (2022).
  • Bowen Li, Xin Peng, Qilin Xiang, Hanzhang Wang, Tao Xie, Jun Sun, Xuanzhe Liu: Enjoy Your Observability: an Industrial Survey of Microservice Tracing and Analysis, Empir. Softw. Eng. 27(1): 25 (2022)
  • Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Wenhai Li, Dan Ding: Delta Debugging Microservice Systems with Parallel Optimization, IEEE Trans. Serv. Comput. 15(1): 16-29 (2022)
2021
  • Tai D. Nguyen, Long H. Pham and Jun Sun: SGUARD: Towards Fixing Vulnerable Smart Contracts Automatically, S&P 2021.
  • Jingyi Wang, Jialuo Chen, Youcheng Sun, Xingjun Ma, Jun Sun and Peng Cheng: RobOT: Robustness-Oriented Testing for Deep Learning Systems, ICSE 2021.
  • Yuqi Chen, Christopher M. Poskitt and Jun Sun: Code Integrity Attestation for PLCs Using Black Box Neural Network Predictions, FSE 2021.
  • Yun Lin, You Seng Ong, Jun Sun, Gordon Fraser, and Jin Song Dong: Graph-based Seed Object Synthesis for Search-Based Unit Testing, FSE 2021.
  • Chi Chen, Xin Peng, Zhenchang Xing, Jun Sun, Xin Wang, Yifan Zhao, and Wenyun Zhao: Holistic Combination of Structural and Textual Code Information for Context based API Recommendation, IEEE Transactions on Software Engineering, 2021.
  • Zhe Zhao, Guangke Chen, Jingyi Wang, Yiwei Yang, Fu Song, and Jun Sun: Attack as Defense: Characterizing Adversarial Examples using Robustness, ISSTA 2021.
  • Ziqi Shuai, Zhenbang Chen, Yufeng Zhang, Jun Sun, and Ji Wang: Type and Interval aware Array Constraint Solving for Symbolic Execution, ISSTA 2021. ACM SIGSOFT Distinguished Paper Award at ISSTA 2021.
  • Yun tang, Yuan Zhou*, Fenghua Wu, Yang Liu, Jun Sun, Wuling Huang, Gang Wang: Route Coverage Testing For Autonomous Vehicles Via Map Modeling, ICRA 2021.
  • Yun Tang, Yuan Zhou, Yang Liu, Jun Sun, Gang Wang: Collision Avoidance Testing for Autonomous Driving Systems on Complete Maps, 2021 IEEE Intelligent Vehicles Symposium (IV). 
  • Richard Schumi and Jun Sun: SpecTest: Specification-Based Compiler Testing, FASE 2021. EASST “Best Paper at ETAPS 2021”.
  • Pengfei Yang, Renjue Li, Jianlin Li, Cheng-Chao Huang, Jingyi Wang, Jun Sun, Bai Xue and Lijun Zhang: Improving Neural Network Verification through Spurious Region Guided Refinement, TACAS 2021. 
  • Bin Hu, Yijian Wu, Xin Peng, Jun Sun, Nanjie Zhan and Jun Wu: Assessing Code Clone Harmfulness: Indicators, Factors, and Counter Measures, SANER 2021.
  • Bing Sun, Jun Sun, Ting Dai and Lijun Zhang: Probablistic Verification of Neural Networks Against Group Fairness, FM 2021.
  • Peixin Zhang, Jingyi Wang, Jun Sun, Xinyu Wang, Guoliang Dong, Xinggen Wang, Ting Dai and Jinsong Dong: Automatic Fairness Testing of Neural Classifiers through Adversarial Sampling, IEEE Transactions on Software Engineering, 2021.
  • Shaohua Zhang, Shuang Liu, Jun Sun, Yuqi Chen, Wenzhi Huang, Jinyi Liu, Jian Liu, and Jianye Hao: FIGCPS: Effective Failure-inducing Input Generation for Cyber-Physical Systems with Deep Reinforcement Learning, ASE 2021. 
  • Bo Gao, Siyuan Shen, Ling Shi, Jiaying Li, Jun Sun and Lei Bu: Verification Assisted Gas Reduction for Smart Contracts, APSEC 2021. Won APSEC 2021 Best Paper.
2020
  • Hugo Bazille, Blaise Genest, Cyrille Jegourel and Jun Sun: Global PAC Bounds for Learning Discrete Time Markov Chains, CAV 2020. 
  • Jiao Jiao, Shuanglong Kan, Shangwei Lin, David Sanan, Yang Liu and Jun Sun: Semantic Understanding of Smart Contracts: Executable Operational Semantics of Solidity, S&P 2020.
  • Duy Tai Nguyen, Long H. Pham, Jun Sun, Yun Lin and Minh Quang Tran: sFuzz: An Efficient Adaptive Fuzzer for Solidity Smart Contracts, ICSE 2020.
  • Peixin Zhang, Jingyi Wang, Jun Sun, Guoliang Dong, Xinyu Wang, Xingen Wang, Jin Song Dong and Dai Ting: White-box Fairness Testing through Adversarial Sampling, ICSE 2020. ACM Distinguished Paper Award and SIGSOFT Research Highlights 2020.
  • Hengbiao Yu, Zhenbang Chen, Xianjin Fu, Ji Wang, Zhendong Su, Jun Sun,  Chun Huang and Wei Dong: Symbolic Verification of Message Passing Interface Programs. ICSE 2020.
  • D. Wang, T. Muller. and Jun Sun: Secure Decision Making with Arbitrarily Malicous Recommendations, In proceedings of The 33rd IEEE Computer Security Foundations Symposium (CSF), 2020.
  • Yuqi Chen, Bohan Xuan, Christopher M. Poskitt, Jun Sun and Fan Zhang: Active Fuzzing for Testing and Securing Cyber-Physical Systems, ISSTA 2020.
  • Yun Lin, Jun Sun, Gordon Fraser, Ziheng Xiu, Ting Liu and Jin Song Dong: Recovering Fitness Gradients for Interprocedural Boolean Flags in Search-Based Testing, ISSTA 2020.
  • Guoliang Dong, Jingyi Wang, Jun Sun, Yang Zhang, Xinyu Wang, Ting Dai, Jin Song Dong and Xingen Wang: Towards Interpreting Recurrent Neural Networks through Probabilistic Abstraction, ASE 2020.
  • Yueling Zhang, Geguang Pu, and Jun Sun: Accelerating All-SAT Computation with Short Blocking Clauses, ASE 2020
  • Haichi Wang, Zan Wang, Jun Sun, Shuang Liu, Ayesha Sadiq, Yuan-Fang Li: Towards Generating Thread-Safe Classes Automatically, ASE 2020.
  • Eric Rothstein-Morris, Jun Sun and Sudipta Chattopadhyay: Systematic Classification of Attackers via Bounded Model Checking, VMCAI 2020.
  • Guanhua Li, Yijian Wu, Chanchal K. Roy, Jun Sun, Xin Peng, Nanjie Zhan, Bin Hu, and Jingyi Ma: SAGA: Efficient and Large-Scale Detection of Near-Miss Clones with GPU Acceleration, SANER 2020.
  • Jiao Jiao, Shang-Wei Lin, and Jun Sun: A General Formal Semantic Framework for Smart Contracts, FASE 2020. 
2019
  • Jingyi Wang, Guoliang Dong, Jun Sun, Xinyu Wang and Zhang Peixin: Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing, ICSE 2019. 
  • Haijun Wang, Yun Lin, Zijiang Yang, Jun Sun, Yang Liu, Jinsong Dong, Qinghua Zheng, Ting Liu: Explaining Regressions via Alignment Slicing and Mending, IEEE Transactions on Software Engineering, 2019. 
  • Yuqi Chen, Chris Poskitt, Jun Sun, Sridhar Adepu and Fan Zhang: Learning-Guided Network Fuzzing for Testing Cyber-Physical System Defences, ASE 2019. 
  • Zan Wang, Yingquan Zhao, Shuang Liu, Jun Sun, Xiang Chen and Huarui Lin: MAP-Coverage: a Novel Coverage Criterion for Testing Thread-Safe Classes, ASE 2019. 
  • Long H. Pham, Quang Loc Le, Quoc-Sang Phan and Jun Sun: Concolic Testing Heap-Manipulating Programs, FM 2019. 
  • Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Dewei Liu, Qilin Xiang and Chuan He: Latent Error Prediction and Fault Localization for Microservice Applications by Learning from System Trace Logs, FSE 2019. 
  • Jingyi Wang, Jun Sun, Shengchao Qin and Cyrille Jegourel: Automatically `Verifying’ Discrete-Time Complex Systems through Learning, Abstraction and Refinement, IEEE Transactions on Software Engineering, 2019. 
  • Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Wenhai Li and Dan Ding: Fault Analysis and Debugging of Microservice Systems: Industrial Survey, Benchmark System, and Empirical Study, IEEE Transactions on Software Engineering, 2019. 
  • Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Wenhai Li, and Dan Ding: Delta Debugging Microservice Systems with Parallel Optimization, IEEE Transactions on Service Computing, 2019. 
  • Flavio Toffalini, Martín Ochoa, Jun Sun and Jianying Zhou: Careful-Packing: A Practical and Scalable Anti-Tampering Software Protection enforced by Trusted Computing, ACM CODASPY 2019. 
  • Long H. Pham, Jun Sun and Quang Loc Le: Compositional Verification of Heap-Manipulating Programs through Property-Guided Learning, APLAS 2019. 
  • Long H. Pham, Quang Loc Le, Quoc-Sang Phan, Jun Sun and Shengchao Qin: Enhancing Symbolic Execution of Heap-based Programs with Separation Logic for Test Input Generation, ATVA 2019. 
  • Étienne André and Jun Sun: Parametric Timed Model Checking for Guaranteeing Timed Opacity, ATVA 2019. 

  • Jialiang Chang, Bo Gao, Hao Xiao, Jun Sun, Yan Cai and Zijiang Yang: sCompile: Critical Path Identification and Analysis for Smart Contracts, ICFEM 2019. 

For publications prior to 2019, kindly refer to DBLP or Google Scholar for their listing.