publications

2024

  1. 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
  2. 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
  3. 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

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

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
  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
  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

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
  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

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
  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

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
  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
  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
  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
  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
  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

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

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