publications

2023

1. DistXplore: Distribution-guided Testing for Evaluating and Enhancing Deep Learning Systems

   Longtian Wang, Xiaofei Xie, Xiaoning Du, Meng Tian, Qing Guo, Zheng Yang, and Chao Shen

   In 31st ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE), 2023

   Bib

   @inproceedings{wang2023distxplore,
     title = {DistXplore: Distribution-guided Testing for Evaluating and Enhancing Deep Learning Systems},
     author = {Wang, Longtian and Xie, Xiaofei and Du, Xiaoning and Tian, Meng and Guo, Qing and Yang, Zheng and Shen, Chao},
     booktitle = {31st ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE)},
     year = {2023},
   }

2. CodeMark: Imperceptible Watermarking for Code Datasets against Neural Code Completion Models

   Zhensun Sun, Xiaoning Du, Fu Song, and Li Li

   In 31st ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE), 2023

   Bib

   @inproceedings{sun2023comark,
     title = {CodeMark: Imperceptible Watermarking for Code Datasets against Neural Code Completion Models},
     author = {Sun, Zhensun and Du, Xiaoning and Song, Fu and Li, Li},
     booktitle = {31st ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE)},
     year = {2023},
   }

3. Don’t Complete It! Preventing Unhelpful Code Completion for Productive and Sustainable Neural Code Completion Systems

   Zhensun Sun, Xiaoning Du, Fu Song, Shangwen Wang, Mingze Ni, and Li Li

   In In 45th International Conference on Software Engineering (ICSE-Poster), 2023, 2023

   Bib PDF

   @inproceedings{sun2023dontcomplete,
     title = {Don't Complete It! Preventing Unhelpful Code Completion for Productive and Sustainable Neural Code Completion Systems},
     author = {Sun, Zhensun and Du, Xiaoning and Song, Fu and Wang, Shangwen and Ni, Mingze and Li, Li},
     booktitle = {In 45th International Conference on Software Engineering (ICSE-Poster), 2023},
     year = {2023},
   }

4. FuzzJIT: Oracle-Enhanced Fuzzing for JavaScript Engine JIT Compiler

   Junjie Wang, Zhiyi Zhang, Shuang Liu, Xiaoning Du, and Junjie Chen

   In The 32nd USENIX Security Symposium (USENIX Security ’23), 2023

   Bib PDF

   @inproceedings{fuzzjit,
     title = {FuzzJIT: Oracle-Enhanced Fuzzing for JavaScript Engine JIT Compiler},
     author = {Wang, Junjie and Zhang, Zhiyi and Liu, Shuang and Du, Xiaoning and Chen, Junjie},
     booktitle = {The 32nd USENIX Security Symposium (USENIX Security '23)},
     year = {2023},
   }

2022

1. Vulnerability Analysis, Robustness Verification, and Mitigation Strategy for Machine Learning-Based Power System Stability Assessment Model Under Adversarial Examples

   Chao Ren, Xiaoning Du, Yan Xu, Qun Song, Yang Liu, and Rui Tan

   IEEE Trans. Smart Grid, 2022
2. Characterizing Python Method Evolution with PyMevol: An Essential Step Towards Enabling Reliable Software Systems

   Haowei Quan, Jiawei Wang, Bo Li, Xiaoning Du, Kui Liu, and Li Li

   In 2022 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW), 2022

   Bib PDF

   @inproceedings{quan2022characterizing,
     title = {Characterizing Python Method Evolution with PyMevol: An Essential Step Towards Enabling Reliable Software Systems},
     author = {Quan, Haowei and Wang, Jiawei and Li, Bo and Du, Xiaoning and Liu, Kui and Li, Li},
     booktitle = {2022 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)},
     pages = {81--86},
     year = {2022},
   }

3. CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning

   Zhensun Sun, Xiaoning Du, Fu Song, Mingze Ni, and Li Li

   In The ACM Web Conference 2022 (WWW), 2022

   Bib PDF Code

   @inproceedings{sun2021coprotector,
     title = {CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning},
     author = {Sun, Zhensun and Du, Xiaoning and Song, Fu and Ni, Mingze and Li, Li},
     booktitle = {The ACM Web Conference 2022 (WWW)},
     year = {2022},
   }

4. On the Importance of Building High-quality Training Datasets for Neural Code Search

   Zhensu Sun, Li Li, Yan Liu, Xiaoning Du, and Li Li

   In 44th International Conference on Software Engineering (ICSE), 2022

   Bib PDF Code

   @inproceedings{sun2022icse,
     title = {On the Importance of Building High-quality Training Datasets for Neural Code Search},
     author = {Sun, Zhensu and Li, Li and Liu, Yan and Du, Xiaoning and Li, Li},
     booktitle = {44th International Conference on Software Engineering (ICSE)},
     year = {2022},
     nomination = {true},
   }

2021

1. Decision-Guided Weighted Automata Extraction from Recurrent Neural Networks

   Xiyue Zhang, Xiaoning Du, Xiaofei Xie, Lei Ma, Yang Liu, and Meng Sun

   In 35th AAAI Conference on Artificial Intelligence, 2021

   Bib PDF

   @inproceedings{zhang2021decision,
     title = {Decision-Guided Weighted Automata Extraction from Recurrent Neural Networks},
     author = {Zhang, Xiyue and Du, Xiaoning and Xie, Xiaofei and Ma, Lei and Liu, Yang and Sun, Meng},
     booktitle = {35th AAAI Conference on Artificial Intelligence},
     volume = {35},
     number = {13},
     pages = {11699--11707},
     year = {2021},
   }

2. Who is real bob? adversarial attacks on speaker recognition systems

   Guangke Chen, Sen Chen, Lingling Fan, Xiaoning Du, Zhe Zhao, Fu Song, and Yang Liu

   In 42nd IEEE Symposium on Security and Privacy (SP), 2021

   Bib PDF Code

   @inproceedings{chen2021real,
     title = {Who is real bob? adversarial attacks on speaker recognition systems},
     author = {Chen, Guangke and Chen, Sen and Fan, Lingling and Du, Xiaoning and Zhao, Zhe and Song, Fu and Liu, Yang},
     booktitle = {42nd IEEE Symposium on Security and Privacy (SP)},
     pages = {694--711},
     year = {2021},
     organization = {IEEE},
   }

2020

1. Towards characterizing adversarial defects of deep learning software from the lens of uncertainty

   Xiyue Zhang, Xiaofei Xie, Lei Ma, Xiaoning Du, Qiang Hu, Yang Liu, Jianjun Zhao, and Meng Sun

   In 42nd IEEE/ACM International Conference on Software Engineering (ICSE), 2020

   Bib PDF

   @inproceedings{zhang2020towards,
     title = {Towards characterizing adversarial defects of deep learning software from the lens of uncertainty},
     author = {Zhang, Xiyue and Xie, Xiaofei and Ma, Lei and Du, Xiaoning and Hu, Qiang and Liu, Yang and Zhao, Jianjun and Sun, Meng},
     booktitle = {42nd IEEE/ACM International Conference on Software Engineering (ICSE)},
     pages = {739--751},
     year = {2020},
     organization = {IEEE},
   }

2. Marble: Model-based robustness analysis of stateful deep learning systems

   Xiaoning Du, Yi Li, Xiaofei Xie, Lei Ma, Yang Liu, and Jianjun Zhao

   In 35th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2020

   Bib PDF Website

   @inproceedings{du2020marble,
     title = {Marble: Model-based robustness analysis of stateful deep learning systems},
     author = {Du, Xiaoning and Li, Yi and Xie, Xiaofei and Ma, Lei and Liu, Yang and Zhao, Jianjun},
     booktitle = {35th IEEE/ACM International Conference on Automated Software Engineering (ASE)},
     pages = {423--435},
     year = {2020},
   }

2019

1. DeepStellar: model-based quantitative analysis of stateful deep learning systems

   Xiaoning Du, Xiaofei Xie, Yi Li, Lei Ma, Yang Liu, and Jianjun Zhao

   In 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE), 2019

   Bib PDF Code Website Demo

   @inproceedings{du2019deepstellar,
     title = {DeepStellar: model-based quantitative analysis of stateful deep learning systems},
     author = {Du, Xiaoning and Xie, Xiaofei and Li, Yi and Ma, Lei and Liu, Yang and Zhao, Jianjun},
     booktitle = {27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE)},
     pages = {477--487},
     year = {2019},
     organization = {ACM},
     demo = {https://www.youtube.com/watch?v=xxKptWPngJA}
   }

2. Marvel: a generic, scalable and effective vulnerability detection platform

   Xiaoning Du

   In 41st IEEE/ACM International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), 2019

   Bib PDF

   @inproceedings{du2019marvel,
     title = {Marvel: a generic, scalable and effective vulnerability detection platform},
     author = {Du, Xiaoning},
     booktitle = {41st IEEE/ACM International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)},
     pages = {129--131},
     year = {2019},
     organization = {IEEE},
   }

3. Devign: effective vulnerability identification by learning comprehensive program semantics via graph neural networks

   Yaqin Zhou, Shangqing Liu, Jingkai Siow, Xiaoning Du, and Yang Liu

   In Advances in Neural Information Processing Systems (NeurIPS), 2019

   Bib PDF

   @inproceedings{zhou2019devign,
     title = {Devign: effective vulnerability identification by learning comprehensive program semantics via graph neural networks},
     author = {Zhou, Yaqin and Liu, Shangqing and Siow, Jingkai and Du, Xiaoning and Liu, Yang},
     booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
     year = {2019},
   }

4. Leopard: Identifying vulnerable code for vulnerability assessment through program metrics

   Xiaoning Du, Bihuan Chen, Yuekang Li, Jianmin Guo, Yaqin Zhou, Yang Liu, and Yu Jiang

   In 41st IEEE/ACM International Conference on Software Engineering (ICSE), 2019

   Bib PDF Website

   @inproceedings{du2019leopard,
     author = {Du, Xiaoning and Chen, Bihuan and Li, Yuekang and Guo, Jianmin and Zhou, Yaqin and Liu, Yang and Jiang, Yu},
     booktitle = {41st IEEE/ACM International Conference on Software Engineering (ICSE)},
     pages = {60--71},
     year = {2019},
     organization = {IEEE},
   }

5. Trace-Length Independent Runtime Monitoring of Quantitative Policies

   Xiaoning Du, Alwen Tiu, Kun Cheng, and Yang Liu

   IEEE Transactions on Dependable and Secure Computing (TDSC) (IF 6.404), 2019

   Bib PDF

   @article{du2019trace,
     title = {Trace-Length Independent Runtime Monitoring of Quantitative Policies},
     author = {Du, Xiaoning and Tiu, Alwen and Cheng, Kun and Liu, Yang},
     journal = {IEEE Transactions on Dependable and Secure Computing (TDSC) (IF 6.404)},
     year = {2019},
     publisher = {IEEE},
   }

6. A Quantitative Analysis Framework for Recurrent Neural Network

   Xiaoning Du, Xiaofei Xie, Yi Li, Lei Ma, Yang Liu, and Jianjun Zhao

   In 34th IEEE/ACM International Conference on Automated Software Engineering (ASE-Tool Demo), 2019

   Bib PDF Demo

   @inproceedings{du2019quantitative,
     title = {A Quantitative Analysis Framework for Recurrent Neural Network},
     author = {Du, Xiaoning and Xie, Xiaofei and Li, Yi and Ma, Lei and Liu, Yang and Zhao, Jianjun},
     booktitle = {34th IEEE/ACM International Conference on Automated Software Engineering (ASE-Tool Demo)},
     pages = {1062--1065},
     year = {2019},
     organization = {IEEE},
     demo = {https://www.youtube.com/watch?v=xxKptWPngJA}
   }

2018

1. Towards Building a Generic Vulnerability Detection Platform by Combining Scalable Attacking Surface Analysis and Directed Fuzzing

   Xiaoning Du

   In International Conference on Formal Engineering Methods, 2018

   Bib PDF

   @inproceedings{du2018towards,
     title = {Towards Building a Generic Vulnerability Detection Platform by Combining Scalable Attacking Surface Analysis and Directed Fuzzing},
     author = {Du, Xiaoning},
     booktitle = {International Conference on Formal Engineering Methods},
     pages = {464--468},
     year = {2018},
     organization = {Springer},
   }

2015

1. Trace-length independent runtime monitoring of quantitative policies in LTL

   Xiaoning Du, Yang Liu, and Alwen Tiu

   In International Symposium on Formal Methods (FM), 2015

   Bib PDF

   @inproceedings{du2015trace,
     title = {Trace-length independent runtime monitoring of quantitative policies in LTL},
     author = {Du, Xiaoning and Liu, Yang and Tiu, Alwen},
     booktitle = {International Symposium on Formal Methods (FM)},
     pages = {231--247},
     year = {2015},
     organization = {Springer, Cham},
   }