Wei Ma

Wei Ma

A Coder, A Researcher, A Scientist

Publications

Full list on Google Scholar. * co-first author

Software Testing, Fuzzing & Analysis

  1. Xu, Hanxiang*; Wei Ma*; Ting Zhou; Yanjie Zhao; Kai Chen; Qiang Hu; Yang Liu; Haoyu Wang. CKGFuzzer: LLM-Based Fuzz Driver Generation Enhanced by Code Knowledge Graph. ICSE 2025, Industry Track (Best Paper Award).
  2. Maoyi Xie; Kaixuan Li; Jingquan Ge; Wei Ma; Yuqiang Sun; Ziqiao Kong; Cen Zhang; Dongge Liu; Oliver Chang; Yang Liu. Arash: Token-Efficient LLM-Assisted Crash Root Cause Analysis in Fuzz Driver Generation. TOSEM, 2026.
  3. Jingquan Ge; Yaowen Zheng; Yuekang Li; Wei Ma; Sheikh Mahbub Habib; Praveen Kakkolangara; Gabriel Wayne Byman; Yang Liu. OptRCA: A More Efficient and Accurate Approach for Automated Root Cause Analysis and Explanation. TOSEM 35(2): 1–32, 2026.
  4. Wei Ma; Thierry Titcheu Chekam; Mike Papadakis; Mark Harman. MuDelta: Delta-Oriented Mutation Testing at Commit Time. ICSE 2021.
  5. Wei Ma; Thomas Laurent; Miloš Ojdanić; Thierry Titcheu Chekam; Anthony Ventresque; Mike Papadakis. Commit-Aware Mutation Testing. ICSME 2020, pp. 394–405 (IEEE Computer Society TCSE Distinguished Paper Award).
  6. Miloš Ojdanić*; Wei Ma*; Thomas Laurent; Thierry Titcheu Chekam; Anthony Ventresque; Mike Papadakis. On the Use of Commit-Relevant Mutants. EMSE 27, 5 (2022).
  7. Cen Zhang; Yaowen Zheng; Mingqiang Bai; Yeting Li; Wei Ma; Xiaofei Xie; Yuekang Li; Limin Sun; Yang Liu. How Effective Are They? Exploring Large Language Model Based Fuzz Driver Generation. ISSTA 2024, pp. 1223–1235.
  8. Qiang Wang; Zhiyuan Hu; Wei Ma; Qiang Chen; Yueling Zhang; Geguang Pu. Runtime Verification of Tactical Data Link. ISSRE 2025, Industry Track (Best Paper Nomination).

AI Security & Trustworthy Systems

  1. Zhihao Lin*; Wei Ma*; Mingyi Zhou; Yanjie Zhao; Haoyu Wang; Yang Liu; Jun Wang; Li Li. MazeBreaker: Multi-Agent Reinforcement Learning for Dynamic Jailbreaking of LLM Security Defenses. ICSE 2026.
  2. Wei Ma; Yu Li; Zhi Chen; Ye Liu; Lingxiao Jiang; Qiang Hu; Junyi Tao. AgentGuard: An Active Threat Discovery System for Package Confusion Using Multi-Agent Collaboration. ML4CS 2025, LNCS 16456, pp. 69–83 (Best Paper Award).
  3. Yu Li; Wei Ma; Zhi Chen; Ye Liu; Lingxiao Jiang; Junyi Tao; Hao Liu; Yongqiang Lyu; Qiang Hu. ConfuScope: A Multi-Agent Framework via Hybrid Search and Content-Aware Analysis for Robust Package Confusion Detection. TSE, 2026.
  4. Wei Ma; Mike Papadakis; Anestis Tsakmalis; Maxime Cordy; Yves Le Traon. Test Selection for Deep Learning Systems. TOSEM 30(2): 1–22, 2021 (ACM TOSEM 2026 Outstanding Paper Award in 5 Years).
  5. Qiang Hu; Yuejun Guo; Xiaofei Xie; Maxime Cordy; Wei Ma; Mike Papadakis; Lei Ma; Yves Le Traon. Assessing the Robustness of Test Selection Methods for Deep Neural Networks. TOSEM, 2025.
  6. Jie Zhang; Wei Ma; Qiang Hu; Shangqing Liu; Xiaofei Xie; Yves Le Traon; Yang Liu. A Black-Box Attack on Code Models via Representation Nearest Neighbor Search. EMNLP Findings 2023, pp. 9706–9716.
  7. Xueqi Dang; Yinghua Li; Wei Ma; et al. Towards Exploring the Limitations of Test Selection Techniques on Graph Neural Networks: An Empirical Study. EMSE 29, 112 (2024).
  8. Qiang Hu; Yuejun Guo; Maxime Cordy; Xiaofei Xie; Wei Ma; Mike Papadakis; Yves Le Traon. Towards Understanding Model Quantization for Reliable Deep Neural Network Deployment. CAIN 2023, pp. 56–67.
  9. Qiang Hu; Yuejun Guo; Maxime Cordy; Xiaofei Xie; Wei Ma; Mike Papadakis; Yves Le Traon. Towards Exploring the Limitations of Active Learning: An Empirical Study. ASE 2022, pp. 917–929.

Software & Web3 Security

  1. Wei Ma; Junjie Shi; Jiaxi Qiu; Cong Wu; Jing Chen; Lingxiao Jiang; Shangqing Liu; Yang Liu; Yang Xiang. Detecting DeFi Fraud With a Graph-Transformer Language Model. IEEE Transactions on Information Forensics and Security 20: 10051–10065, 2025.
  2. Wei Ma; Chenguang Zhu; Ye Liu; Xiaofei Xie; Yi Li. A Comprehensive Study of Governance Issues in Decentralized Finance Applications. TOSEM, 2025.
  3. Wei Ma; Daoyuan Wu; Yuqiang Sun; Tianwen Wang; Shangqing Liu; Jian Zhang; Yue Xue; Yang Liu. Combining Fine-tuning and LLM-Based Agents for Intuitive Smart Contract Auditing with Justifications. ICSE 2025.
  4. Ye Liu; Yuqing Niu; Chengyan Ma; Ruidong Han; Wei Ma; Yi Li; Debin Gao; David Lo. Towards Secure Program Partitioning for Smart Contracts With LLM’s In-Context Learning. TSE, 2026.
  5. Dianxiang Sun; Wei Ma; Liming Nie; Yang Liu. SoK: A Taxonomic Analysis of DeFi Rug Pulls: Types, Dataset, and Tool Assessment. Proc. ACM Softw. Eng. 2 (ISSTA): 550–572, 2025.
  6. Jian Zhang; Chong Wang; Anran Li; Weisong Sun; Cen Zhang; Wei Ma; Yang Liu. Evaluating Large Language Models for Line-Level Vulnerability Localization. TSE 52(3): 770–785, 2026.
  7. Shangqing Liu; Wei Ma; Jian Wang; Xiaofei Xie; Ruitao Feng; Yang Liu. Enhancing Code Vulnerability Detection via Vulnerability-Preserving Data Augmentation. LCTES 2024, pp. 166–177.

Foundations of Code LLMs & Software Agents

  1. Zhi Chen; Wei Ma; Lingxiao Jiang. Beyond Final Code: A Process-Oriented Error Analysis of Software Development Agents in Real-World GitHub Scenarios. ICSE 2026.
  2. Wei Ma; Zhi Chen; Jingxu Gu; Tianling Li; Shangqing Liu; Lingxiao Jiang. Same Signal, Different Semantics: A Cross-Framework Behavioral Analysis of Software Engineering Agents. arXiv:2605.18332, 2026.
  3. Xiaoning Ren; Qiang Hu; Wei Ma; Chongyang Liu; Yan Li; Yao Zhang; Lingxiao Jiang; Yongqiang Lyu; Yinxing Xue. ProCURE: Addressing the Programming Concept Understanding Gap for Code Generation in LLMs via Concept-Aware Consistency Learning. IJCAI 2026.
  4. Wei Ma; Shangqing Liu; Mengjie Zhao; Xiaofei Xie; Wenhan Wang; Qiang Hu; Jie Zhang; Yang Liu. Unveiling Code Pre-Trained Models: Investigating Syntax and Semantics Capacities. TOSEM 33(7): 1–29, 2024.
  5. Wei Ma*; Mengjie Zhao*; Ezekiel Soremekun; Qiang Hu; Jie M. Zhang; Mike Papadakis; Maxime Cordy; Xiaofei Xie; Yves Le Traon. GraphCode2Vec: Generic Code Embedding via Lexical and Program Dependence Analyses. MSR 2022, pp. 524–536.
  6. Zhihao Lin*; Wei Ma*; Tao Lin; Yaowen Zheng; Jingquan Ge; Jun Wang; Jacques Klein; Tegawendé Bissyandé; Yang Liu; Li Li. Open-Source AI-Based SE Tools: Opportunities and Challenges of Collaborative Software Learning. TOSEM, 2025.
  7. Shangqing Liu; Daya Guo; Jian Zhang; Wei Ma; Yanzhou Li; Yang Liu. An Empirical Study of Exploring the Capabilities of Large Language Models in Code Learning. TSE, 2025.
  8. Shangqing Liu; Yanzhou Li; Xiaofei Xie; Wei Ma; Guozhu Meng; Yang Liu. Automated Commit Intelligence by Pre-training. TOSEM 33(8), Article 201, 2024.
  9. Zhihao Lin; Mingyi Zhou; Wei Ma; Chi Chen; Yun Yang; Jun Wang; Chunming Hu; Li Li. HapRepair: Learn to Repair OpenHarmony Apps. FSE Companion 2025, Industry Track, pp. 319–330.
  10. Junjie Shi; Wei Ma; Chi Chen; Lingxiao Jiang. Debugging for LLM-Based Software. FSE 2025, FSE 2030 Workshop.
  11. Tianlin Li; Qiang Hu; Chong Wang; Jian Zhang; Wei Ma; Aishan Liu; Jingyi Wang; Yang Liu. An Analytical Perspective on Software Engineering for Large Language Models. ICECCS 2025, pp. 489–494.
  12. Yao Zhang; Yude Bai; Minhong Dong; Keqing Cen; Ji Zhang; Qiang Hu; Wei Ma; Yongqiang Lyu; Ruitao Feng; Xiaohong Li; Junjie Wang; Lingxiao Jiang; Yang Liu. LIMR: Intent-Aware Mashup API Recommendation via LLM-Augmented Multi-Scale Fusion. IEEE Transactions on Services Computing, 2026.
  13. Wenhan Wang; Yanzhou Li; Anran Li; Jian Zhang; Wei Ma; Yang Liu. An Empirical Study on Noisy Label Learning for Program Understanding. ICSE 2024, Article 95, pp. 1–12.