Site Overlay

Publications

By admin
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.
  • 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.
  • Shunkai Zhu, Jingyi Wang, Jun Sun, Jie Yang, Xingwei Lin, Liyi Zhang, and Peng Cheng: “Better Pay Attention Whilst Fuzzing”, TOSEM 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”, TOSEM 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”, TOSEM 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”, TOSEM 2023.
  • Yuan Zhou, Yang Sun, Yun Tang, Yuqi Chen, and Jun Sun: “Specification-based Autonomous Driving System Testing”, TSE 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”, TSE 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”, TOSEM 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.
  • 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”, TOSEM 2022.
  • Yingquan Zhao, Zan Wang, Shuang Liu, Jun Sun, Junjie Chen, Xiang Chen: “Achieving High MAP-Coverage through Pattern Constraint Reduction”, TSE 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”, TSE 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”, TSE 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.