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Wei Ma 0014
Person information
- affiliation: NTU, Singapore
Other persons with the same name
- Wei Ma — disambiguation page
- Wei Ma 0001
— Shenzhen University, Shenzhen, China
- Wei Ma 0002
- Wei Ma 0003
- Wei Ma 0004
- Wei Ma 0005
- Wei Ma 0006
- Wei Ma 0007
- Wei Ma 0008
- Wei Ma 0009
- Wei Ma 0010
- Wei Ma 0011
- Wei Ma 0012
- Wei Ma 0013
- Wei Ma 0015
- Wei Ma 0016
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2020 – today
- 2026
- [j14]Jingquan Ge
OptRCA: A More Efficient and Accurate Approach for Automated Root Cause Analysis and Explanation. ACM Trans. Softw. Eng. Methodol. 35(2): 43:1-43:32 (2026) - [j13]Jian Zhang
Evaluating Large Language Models for Line-Level Vulnerability Localization. IEEE Trans. Software Eng. 52(3): 770-785 (2026) - [j12]Ye Liu
Towards Secure Program Partitioning for Smart Contracts With LLM's In-Context Learning. IEEE Trans. Software Eng. 52(4): 1549-1567 (2026) - 2025
- [j11]Dianxiang Sun
SoK: A Taxonomic Analysis of DeFi Rug Pulls: Types, Dataset, and Tool Assessment. Proc. ACM Softw. Eng. 2(ISSTA): 550-572 (2025) - [j10]Wei Ma
Detecting DeFi Fraud With a Graph-Transformer Language Model. IEEE Trans. Inf. Forensics Secur. 20: 10051-10065 (2025) - [j9]Zhihao Lin
Open Source AI-based SE Tools: Opportunities and Challenges of Collaborative Software Learning. ACM Trans. Softw. Eng. Methodol. 34(5): 126:1-126:24 (2025) - [j8]Qiang Hu
Assessing the Robustness of Test Selection Methods for Deep Neural Networks. ACM Trans. Softw. Eng. Methodol. 34(7): 195:1-195:26 (2025) - [j7]Wei Ma
A Comprehensive Study of Governance Issues in Decentralized Finance Applications. ACM Trans. Softw. Eng. Methodol. 34(7): 208:1-208:31 (2025) - [j6]Shangqing Liu
An Empirical Study of Exploring the Capabilities of Large Language Models in Code Learning. IEEE Trans. Software Eng. 51(11): 3088-3102 (2025) - [c13]Tianlin Li
An Analytical Perspective on Software Engineering for Large Language Models. ICECCS 2025: 489-494 - [c12]Hanxiang Xu, 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 Companion 2025: 243-254 - [c11]Wei Ma, Daoyuan Wu
Combining Fine-Tuning and LLM-Based Agents for Intuitive Smart Contract Auditing with Justifications. ICSE 2025: 1742-1754 - [c10]Zhihao Lin
HapRepair: Learn to Repair OpenHarmony Apps. SIGSOFT FSE Companion 2025: 319-330 - [i22]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. CoRR abs/2502.14215 (2025) - [i21]Wei Ma, Yixiao Yang, Qiang Hu, Shi Ying, Zhi Jin, Bo Du, Zhenchang Xing, Tianlin Li, Junjie Shi, Yang Liu, Linxiao Jiang:
Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol. CoRR abs/2508.20737 (2025) - [i20]Weizhe Wang, Wei Ma, Qiang Hu, Yao Zhang, Jianfei Sun, Bin Wu, Yang Liu, Guangquan Xu, Lingxiao Jiang:
VulnRepairEval: An Exploit-Based Evaluation Framework for Assessing Large Language Model Vulnerability Repair Capabilities. CoRR abs/2509.03331 (2025) - [i19]Wei Ma, Yixiao Yang, Jingquan Ge, Xiaofei Xie, Lingxiao Jiang:
Prompt Stability in Code LLMs: Measuring Sensitivity across Emotion- and Personality-Driven Variations. CoRR abs/2509.13680 (2025) - 2024
- [j5]Xueqi Dang
Towards Exploring the Limitations of Test Selection Techniques on Graph Neural Networks: An Empirical Study. Empir. Softw. Eng. 29(5): 112 (2024) - [j4]Wei Ma
Unveiling Code Pre-Trained Models: Investigating Syntax and Semantics Capacities. ACM Trans. Softw. Eng. Methodol. 33(7): 169:1-169:29 (2024) - [j3]Shangqing Liu
Automated Commit Intelligence by Pre-training. ACM Trans. Softw. Eng. Methodol. 33(8): 201:1-201:30 (2024) - [c9]Wenhan Wang
An Empirical Study on Noisy Label Learning for Program Understanding. ICSE 2024: 95:1-95:12 - [c8]Cen Zhang
How Effective Are They? Exploring Large Language Model Based Fuzz Driver Generation. ISSTA 2024: 1223-1235 - [c7]Shangqing Liu
Enhancing Code Vulnerability Detection via Vulnerability-Preserving Data Augmentation. LCTES 2024: 166-177 - [i18]Yuqiang Sun
LLM4Vuln: A Unified Evaluation Framework for Decoupling and Enhancing LLMs' Vulnerability Reasoning. CoRR abs/2401.16185 (2024) - [i17]Wei Ma, Daoyuan Wu, Yuqiang Sun
Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications. CoRR abs/2403.16073 (2024) - [i16]Dianxiang Sun, Wei Ma, Liming Nie, Yang Liu:
SoK: Comprehensive Analysis of Rug Pull Causes, Datasets, and Detection Tools in DeFi. CoRR abs/2403.16082 (2024) - [i15]Jian Zhang, Chong Wang, Anran Li, Weisong Sun, Cen Zhang, Wei Ma, Yang Liu:
An Empirical Study of Automated Vulnerability Localization with Large Language Models. CoRR abs/2404.00287 (2024) - [i14]Zhihao Lin, Wei Ma, Tao Lin, Yaowen Zheng, Jingquan Ge, Jun Wang, Jacques Klein, Tegawendé F. Bissyandé, Yang Liu, Li Li
Open-Source AI-based SE Tools: Opportunities and Challenges of Collaborative Software Learning. CoRR abs/2404.06201 (2024) - [i13]Shangqing Liu, Wei Ma, Jian Wang, Xiaofei Xie
Enhancing Code Vulnerability Detection via Vulnerability-Preserving Data Augmentation. CoRR abs/2404.09599 (2024) - [i12]Zhihao Lin, Wei Ma, Mingyi Zhou, Yanjie Zhao, Haoyu Wang, Yang Liu
PathSeeker: Exploring LLM Security Vulnerabilities with a Reinforcement Learning-Based Jailbreak Approach. CoRR abs/2409.14177 (2024) - [i11]Hanxiang Xu, Wei Ma, Ting Zhou, Yanjie Zhao, Kai Chen, Qiang Hu, Yang Liu, Haoyu Wang:
A Code Knowledge Graph-Enhanced System for LLM-Based Fuzz Driver Generation. CoRR abs/2411.11532 (2024) - 2023
- [c6]Qiang Hu, Yuejun Guo, Maxime Cordy, Xiaofei Xie
Towards Understanding Model Quantization for Reliable Deep Neural Network Deployment. CAIN 2023: 56-67 - [c5]Jie Zhang, Wei Ma, Qiang Hu, Shangqing Liu, Xiaofei Xie
A Black-Box Attack on Code Models via Representation Nearest Neighbor Search. EMNLP (Findings) 2023: 9706-9716 - [i10]Jie Zhang, Wei Ma, Qiang Hu, Xiaofei Xie
RNNS: Representation Nearest Neighbor Search Black-Box Attack on Code Models. CoRR abs/2305.05896 (2023) - [i9]Wei Ma, Shangqing Liu, Wenhan Wang, Qiang Hu, Ye Liu, Cen Zhang, Liming Nie, Yang Liu
The Scope of ChatGPT in Software Engineering: A Thorough Investigation. CoRR abs/2305.12138 (2023) - [i8]Wenhan Wang, Yanzhou Li, Anran Li, Jian Zhang, Wei Ma, Yang Liu:
An Empirical Study on the Effectiveness of Noisy Label Learning for Program Understanding. CoRR abs/2307.08990 (2023) - [i7]Cen Zhang, Mingqiang Bai, Yaowen Zheng, Yeting Li, Xiaofei Xie
Understanding Large Language Model Based Fuzz Driver Generation. CoRR abs/2307.12469 (2023) - [i6]Qiang Hu, Yuejun Guo, Xiaofei Xie
Evaluating the Robustness of Test Selection Methods for Deep Neural Networks. CoRR abs/2308.01314 (2023) - [i5]Wei Ma, Chenguang Zhu, Ye Liu, Xiaofei Xie
A Comprehensive Study of Governance Issues in Decentralized Finance Applications. CoRR abs/2311.01433 (2023) - 2022
- [j2]Milos Ojdanic
On the use of commit-relevant mutants. Empir. Softw. Eng. 27(5): 114 (2022) - [c4]Wei Ma, Mengjie Zhao
GraphCode2Vec: Generic Code Embedding via Lexical and Program Dependence Analyses. MSR 2022: 524-536 - [i4]Qiang Hu, Yuejun Guo, Maxime Cordy, Xiaofei Xie
Characterizing and Understanding the Behavior of Quantized Models for Reliable Deployment. CoRR abs/2204.04220 (2022) - [i3]Wei Ma, Mengjie Zhao, Xiaofei Xie
Is Self-Attention Powerful to Learn Code Syntax and Semantics? CoRR abs/2212.10017 (2022) - 2021
- [j1]Wei Ma, Mike Papadakis
Test Selection for Deep Learning Systems. ACM Trans. Softw. Eng. Methodol. 30(2): 13:1-13:22 (2021) - [c3]Wei Ma, Thierry Titcheu Chekam, Mike Papadakis
MuDelta: Delta-Oriented Mutation Testing at Commit Time. ICSE 2021: 897-909 - [c2]Qiang Hu, Yuejun Guo
Towards Exploring the Limitations of Active Learning: An Empirical Study. ASE 2021: 917-929 - [i2]Wei Ma, Mengjie Zhao, Ezekiel O. Soremekun, Qiang Hu, Jie Zhang, Mike Papadakis, Maxime Cordy, Xiaofei Xie, Yves Le Traon:
GraphCode2Vec: Generic Code Embedding via Lexical and Program Dependence Analyses. CoRR abs/2112.01218 (2021) - 2020
- [c1]Wei Ma, Thomas Laurent
Commit-Aware Mutation Testing. ICSME 2020: 394-405
2010 – 2019
- 2019
- [i1]Wei Ma, Mike Papadakis, Anestis Tsakmalis, Maxime Cordy, Yves Le Traon:
Test Selection for Deep Learning Systems. CoRR abs/1904.13195 (2019)
Coauthor Index
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last updated on 2026-05-10 01:48 CEST by the dblp team
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