@inproceedings{Zhensu24TOSEM,
title = {Don't Complete It! Preventing Unhelpful Code Completion for Productive and Sustainable Neural Code Completion Systems},
author = {Sun, Zhensu and Du, Xiaoning and Song, Fu and Wang, Shangwen and Ni, Mingze and Li, Li and Lo, David},
booktitle = {ACM Transactions on Software Engineering and Methodology (TOSEM)},
year = {2024},
}
FDI: Attack Neural Code Generation Systems through User Feedback Channel
Zhensu Sun, Xiaoning Du, Xiapu Luo, Fu Song, David Lo, and Li Li
In 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), 2024
@inproceedings{Zhensu24ISSTAa,
title = {FDI: Attack Neural Code Generation Systems through User Feedback Channel},
author = {Sun, Zhensu and Du, Xiaoning and Luo, Xiapu and Song, Fu and Lo, David and Li, Li},
booktitle = {33rd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA)},
year = {2024},
}
AI Coders Are Among Us: Rethinking Programming Language Grammar Towards Efficient Code Generation
Zhensu Sun, Xiaoning Du, Zhou Yang, Li Li, and David Lo
In 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), 2024
@inproceedings{Zhensu24ISSTAb,
title = {AI Coders Are Among Us: Rethinking Programming Language Grammar Towards Efficient Code Generation},
author = {Sun, Zhensu and Du, Xiaoning and Yang, Zhou and Li, Li and Lo, David},
booktitle = {33rd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA)},
year = {2024},
award = {ACM SIGSOFT Distinguished Paper Award}
}
Can Graph Database Systems Correctly Handle Writing Operations? A Metamorphic Testing Approach with Graph-State Persistence Oracle
Shuang Liu, Junhao Lan, Xiaoning Du, Jiyuan Li, Wei Lu, Jiajun Jiang, and Xiaoyong Du
In 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), 2024
@inproceedings{Shuang24ISSTA,
title = {Can Graph Database Systems Correctly Handle Writing Operations? A Metamorphic Testing Approach with Graph-State Persistence Oracle},
author = {Liu, Shuang and Lan, Junhao and Du, Xiaoning and Li, Jiyuan and Lu, Wei and Jiang, Jiajun and Du, Xiaoyong},
booktitle = {33rd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA)},
year = {2024},
}
Are Latent Vulnerabilities Hidden Gems for Software Vulnerability Prediction? An Empirical Study
Triet Le, Xiaoning Du, and M. Ali Babar
In 21st International Conference on Mining Software Repositories (MSR), 2024
@inproceedings{Triet24msr,
title = {Are Latent Vulnerabilities Hidden Gems for Software Vulnerability Prediction? An Empirical Study},
author = {Le, Triet and Du, Xiaoning and Babar, M. Ali},
booktitle = {21st International Conference on Mining Software Repositories (MSR)},
year = {2024},
}
WasmCFuzz: Structure-aware Fuzzing for Wasm Compilers
Xiangwei Zhang, Junjie Wang, Xiaoning Du, and Shuang Liu
In Joint Workshop the International Workshop on Engineering and Security of Critical Systems (EnCyCriS) and the International Workshop on Software Vulnerability Management (SVM) (co-located with ICSE 2024), 2024
@inproceedings{xiangwei24svm,
title = {WasmCFuzz: Structure-aware Fuzzing for Wasm Compilers},
author = {Zhang, Xiangwei and Wang, Junjie and Du, Xiaoning and Liu, Shuang},
booktitle = {Joint Workshop the International Workshop on Engineering and Security of Critical Systems (EnCyCriS) and the International Workshop on Software Vulnerability Management (SVM) (co-located with ICSE 2024)},
year = {2024},
}
When Neural Code Completion Models Size up the Situation: Attaining Cheaper and Faster Completion through Dynamic Model Inference
Zhensun Sun, Xiaoning Du, Fu Song, Shangwen Wang, and Li Li
In 46th International Conference on Software Engineering (ICSE), 2024
@inproceedings{sun2024dynamicinference,
title = {When Neural Code Completion Models Size up the Situation: Attaining Cheaper and Faster Completion through Dynamic Model Inference},
author = {Sun, Zhensun and Du, Xiaoning and Song, Fu and Wang, Shangwen and Li, Li},
booktitle = {46th International Conference on Software Engineering (ICSE)},
year = {2024},
}
2023
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
@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},
}
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
@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},
}
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 45th International Conference on Software Engineering (ICSE-Poster), 2023, 2023
@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 = {45th International Conference on Software Engineering (ICSE-Poster), 2023},
year = {2023},
}
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
@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
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
@article{Ren00S0T22,
author = {Ren, Chao and Du, Xiaoning and Xu, Yan and Song, Qun and Liu, Yang and Tan, Rui},
title = {Vulnerability Analysis, Robustness Verification, and Mitigation Strategy for Machine Learning-Based Power System Stability Assessment Model Under Adversarial Examples},
journal = {{IEEE} Trans. Smart Grid},
volume = {13},
number = {2},
pages = {1622--1632},
year = {2022},
}
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
@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},
}
CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning
Zhensun Sun, Xiaoning Du, Fu Song, Mingze Ni, and Li Li
@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},
}
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
@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},
award = {ACM SIGSOFT Distinguished Paper Award nomination},
}
2021
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
@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},
}
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
@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
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
@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},
}
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
@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
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
@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}
}
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
@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},
}
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
@inproceedings{du2019leopard,
title = {Leopard: Identifying vulnerable code for vulnerability assessment through program metrics},
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},
}
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
@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},
}
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
@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
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