An Empirical Study on the Effect of Dynamic Slicing on Automated Program Repair Efficiency. - Anbang Guo; Xiaoguang Mao; Deheng Yang; Shangwen Wang (ICSME, 2018)

A Hybrid Approach for Tag Hierarchy Construction. - Shangwen Wang; Tao Wang 006; Xiaoguang Mao; Gang Yin; Yue Yu 001 (ICSR, 2018)

An Initial Step Towards Organ Transplantation Based on GitHub Repository. - Shangwen Wang; Xiaoguang Mao; Yue Yu 001 (IEEE Access, 2018)

Multi-Location Program Repair: Roads Ahead. - Shangwen Wang; Xiaoguang Mao; Nan Niu; Xin Yi; Anbang Guo (CoRR, 2018)

Attention Please: Consider Mockito when Evaluating Newly Released Automated Program Repair Techniques. - Shangwen Wang; Ming Wen 001; Deheng Yang; Xiaoguang Mao (CoRR, 2018)

Attention Please: Consider Mockito when Evaluating Newly Proposed Automated Program Repair Techniques. - Shangwen Wang; Ming Wen 001; Xiaoguang Mao; Deheng Yang (EASE, 2019)

How Different Is It Between Machine-Generated and Developer-Provided Patches? : An Empirical Study on the Correct Patches Generated by Automated Program Repair Techniques. - Shangwen Wang; Ming Wen 001; Liqian Chen; Xin Yi; Xiaoguang Mao (ESEM, 2019)

Multi-Location Program Repair Strategies Learned from Successful Experience (S). - Shangwen Wang; Xiaoguang Mao; Nan Niu; Xin Yi; Anbang Guo (SEKE, 2019)

Dissection on Java Organs in GitHub Repositories. - Shangwen Wang; Xiaoguang Mao; Xin Yi (IEEE Access, 2019)

History-Driven Fix for Code Quality Issues. - Jiangtao Xue; Xinjun Mao; Yao Lu 003; Yue Yu 001; Shangwen Wang (IEEE Access, 2019)

Understanding the Non-Repairability Factors of Automated Program Repair Techniques. - Bo Lin; Shangwen Wang; Ming Wen 001; Zhang Zhang 005; Hongjun Wu; Yihao Qin; Xiaoguang Mao (APSEC, 2020)

An Empirical Study on the Influence of Social Interactions for the Acceptance of Answers in Stack Overflow. - Zhang Zhang 005; Xinjun Mao; Yao Lu 003; Shangwen Wang; Jinyu Lu (APSEC, 2020)

On the efficiency of test suite based program repair: A Systematic Assessment of 16 Automated Repair Systems for Java Programs. - Kui Liu 001; Shangwen Wang; Anil Koyuncu; Kisub Kim; Tegawendé F. Bissyandé; Dongsun Kim 001; Peng Wu; Jacques Klein; Xiaoguang Mao; Yves Le Traon (ICSE, 2020)

Automated Patch Correctness Assessment: How Far are We? - Shangwen Wang; Ming Wen 001; Bo Lin; Hongjun Wu; Yihao Qin; Deqing Zou; Xiaoguang Mao; Hai Jin 001 (ASE, 2020)

Large-Scale Manual Validation of Bug Fixing Commits: A Fine-grained Analysis of Tangling. - Steffen Herbold; Alexander Trautsch; Benjamin Ledel; Alireza Aghamohammadi; Taher Ahmed Ghaleb; Kuljit Kaur Chahal; Tim Bossenmaier; Bhaveet Nagaria; Philip Makedonski; Matin Nili Ahmadabadi; Kristóf Szabados; Helge Spieker; et al. (CoRR, 2020)

Peculiar: Smart Contract Vulnerability Detection Based on Crucial Data Flow Graph and Pre-training Techniques. - Hongjun Wu; Zhuo Zhang 007; Shangwen Wang; Yan Lei; Bo Lin; Yihao Qin; Haoyu Zhang; Xiaoguang Mao (ISSRE, 2021)

Automated Comment Update: How Far are We? - Bo Lin; Shangwen Wang; Kui Liu 001; Xiaoguang Mao; Tegawendé F. Bissyandé (ICPC, 2021)

Lightweight global and local contexts guided method name recommendation with prior knowledge. - Shangwen Wang; Ming Wen 001; Bo Lin; Xiaoguang Mao (ESEC/SIGSOFT FSE, 2021)

On the Impact of Flaky Tests in Automated Program Repair. - Yihao Qin; Shangwen Wang; Kui Liu 001; Xiaoguang Mao; Tegawendé F. Bissyandé (SANER, 2021)

Beep: Fine-grained Fix Localization by Learning to Predict Buggy Code Elements. - Shangwen Wang; Kui Liu 001; Bo Lin; Li Li 029; Jacques Klein; Xiaoguang Mao; Tegawendé F. Bissyandé (CoRR, 2021)

Peeler: Learning to Effectively Predict Flakiness without Running Tests. - Yihao Qin; Shangwen Wang; Kui Liu 001; Bo Lin; Hongjun Wu; Li Li 029; Xiaoguang Mao; Tegawendé F. Bissyandé (ICSME, 2022)

Fine-grained code-comment semantic interaction analysis. - Mingyang Geng; Shangwen Wang; Dezun Dong; Shanzhi Gu; Fang Peng; Weijian Ruan; Xiangke Liao (ICPC, 2022)

Reentrancy Vulnerability Detection and Localization: A Deep Learning Based Two-phase Approach. - Zhuo Zhang 007; Yan Lei; Meng Yan 001; Yue Yu 001; Jiachi Chen; Shangwen Wang; Xiaoguang Mao (ASE, 2022)

Is this Change the Answer to that Problem?: Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness. - Haoye Tian; Xunzhu Tang; Andrew Habib; Shangwen Wang; Kui Liu 001; Xin Xia 001; Jacques Klein; Tegawendé F. Bissyandé (ASE, 2022)

On the Way to Microservices: Exploring Problems and Solutions from Online Q&A Community. - Menghan Wu; Yang Zhang 026; Jiakun Liu; Shangwen Wang; Zhang Zhang 005; Xin Xia 001; Xinjun Mao (SANER, 2022)

Recommending Base Image for Docker Containers based on Deep Configuration Comprehension. - Yinyuan Zhang; Yang Zhang 026; Xinjun Mao; Yiwen Wu 001; Bo Lin; Shangwen Wang (SANER, 2022)

Learning to Prevent Profitless Neural Code Completion. - Zhensu Sun; Xiaoning Du 001; Fu Song; Shangwen Wang; Mingze Ni; Li Li 029 (CoRR, 2022)

A fine-grained data set and analysis of tangling in bug fixing commits. - Steffen Herbold; Alexander Trautsch; Benjamin Ledel; Alireza Aghamohammadi; Taher Ahmed Ghaleb; Kuljit Kaur Chahal; Tim Bossenmaier; Bhaveet Nagaria; Philip Makedonski; Matin Nili Ahmadabadi; Kristóf Szabados; Helge Spieker; et al. (Empir. Softw. Eng., 2022)

Context-Aware Code Change Embedding for Better Patch Correctness Assessment. - Bo Lin; Shangwen Wang; Ming Wen 001; Xiaoguang Mao (ACM Trans. Softw. Eng. Methodol., 2022)

Don't Complete It! Preventing Unhelpful Code Completion for Productive and Sustainable Neural Code Completion Systems. - Zhensu Sun; Xiaoning Du 001; Fu Song; Shangwen Wang; Mingze Ni; Li Li 029 (ICSE Companion, 2023)

Interpretation-based Code Summarization. - Mingyang Geng; Shangwen Wang; Dezun Dong; Haotian Wang 001; Shaomeng Cao; Kechi Zhang; Zhi Jin (ICPC, 2023)

An Extensive Study of the Structure Features in Transformer-based Code Semantic Summarization. - Kang Yang 001; Xinjun Mao; Shangwen Wang; Yihao Qin; Tanghaoran Zhang; Yao Lu 003; Kamal Al-Sabahi (ICPC, 2023)

An Extensive Study on Adversarial Attack against Pre-trained Models of Code. - Xiaohu Du; Ming Wen 001; Zichao Wei; Shangwen Wang; Hai Jin 001 (ESEC/SIGSOFT FSE, 2023)

CCT5: A Code-Change-Oriented Pre-trained Model. - Bo Lin; Shangwen Wang; Zhongxin Liu 002; Yepang Liu 001; Xin Xia 001; Xiaoguang Mao (ESEC/SIGSOFT FSE, 2023)

Natural Language to Code: How Far Are We? - Shangwen Wang; Mingyang Geng; Bo Lin; Zhensu Sun; Ming Wen 001; Yepang Liu 001; Li Li 029; Tegawendé F. Bissyandé; Xiaoguang Mao (ESEC/SIGSOFT FSE, 2023)

An Empirical Study on Using Large Language Models for Multi-Intent Comment Generation. - Mingyang Geng; Shangwen Wang; Dezun Dong; Haotian Wang 001; Ge Li 001; Zhi Jin; Xiaoguang Mao; Xiangke Liao (CoRR, 2023)

FITNESS: A Causal De-correlation Approach for Mitigating Bias in Machine Learning Software. - Ying Xiao; Shangwen Wang; Sicen Liu; Dingyuan Xue; Xian Zhan; Yepang Liu 001 (CoRR, 2023)

Enhancing Code Intelligence Tasks with ChatGPT. - Kang Yang 001; Xinjun Mao; Shangwen Wang; Tanghaoran Zhang; Bo Lin; Yanlin Wang 001; Yihao Qin; Zhang Zhang 005; Xiaoguang Mao (CoRR, 2023)

Predictive Comment Updating With Heuristics and AST-Path-Based Neural Learning: A Two-Phase Approach. - Bo Lin; Shangwen Wang; Zhongxin Liu 002; Xin Xia 001; Xiaoguang Mao (IEEE Trans. Software Eng., 2023)

Two Birds with One Stone: Boosting Code Generation and Code Search via a Generative Adversarial Network. - Shangwen Wang; Bo Lin; Zhensu Sun; Ming Wen 001; Yepang Liu 001; Yan Lei; Xiaoguang Mao (Proc. ACM Program. Lang., 2023)

Pre-implementation Method Name Prediction for Object-oriented Programming. - Shangwen Wang; Ming Wen 001; Bo Lin; Yepang Liu 001; Tegawendé F. Bissyandé; Xiaoguang Mao (ACM Trans. Softw. Eng. Methodol., 2023)

Learning Feasible Causal Algorithmic Recourse without Prior Structure. - Haotian Wang 001; Hao Zou 001; Xueguang Zhou; Shangwen Wang; Long Lan; Wenjing Yang 002; Peng Cui 001 (ICDM (Workshops), 2024)

Large Language Models are Few-Shot Summarizers: Multi-Intent Comment Generation via In-Context Learning. - Mingyang Geng; Shangwen Wang; Dezun Dong; Haotian Wang 001; Ge Li 001; Zhi Jin; Xiaoguang Mao; Xiangke Liao (ICSE, 2024)

When Neural Code Completion Models Size up the Situation: Attaining Cheaper and Faster Completion through Dynamic Model Inference. - Zhensu Sun; Xiaoning Du 001; Fu Song; Shangwen Wang; Li Li 029 (ICSE, 2024)

One Size Does Not Fit All: Multi-granularity Patch Generation for Better Automated Program Repair. - Bo Lin; Shangwen Wang; Ming Wen 001; Liqian Chen; Xiaoguang Mao (ISSTA, 2024)

CAREER: Context-Aware API Recognition with Data Augmentation for API Knowledge Extraction. - Zhang Zhang 005; Xinjun Mao; Shangwen Wang; Kang Yang 001; Yao Lu 003 (ICPC, 2024)

AgentFL: Scaling LLM-based Fault Localization to Project-Level Context. - Yihao Qin; Shangwen Wang; Yiling Lou; Jinhao Dong; Kaixin Wang; Xiaoling Li 002; Xiaoguang Mao (CoRR, 2024)

Identifying Knowledge Editing Types in Large Language Models. - Xiaopeng Li 006; Shangwen Wang; Shezheng Song; Bin Ji 002; Huijun Liu 003; Shasha Li 001; Jun Ma 015; Jie Yu 008 (CoRR, 2024)

Fault Localization from the Semantic Code Search Perspective. - Yihao Qin; Shangwen Wang; Yan Lei; Zhuo Zhang 007; Bo Lin; Xin Peng; Liqian Chen; Xiaoguang Mao (CoRR, 2024)

There are More Fish in the Sea: Automated Vulnerability Repair via Binary Templates. - Bo Lin; Shangwen Wang; Liqian Chen; Xiaoguang Mao (CoRR, 2024)

Keep It Simple: Towards Accurate Vulnerability Detection for Large Code Graphs. - Xin Peng; Shangwen Wang; Yihao Qin; Bo Lin; Liqian Chen; Xiaoguang Mao (CoRR, 2024)

LSAQ: Layer-Specific Adaptive Quantization for Large Language Model Deployment. - Binrui Zeng; Bin Ji 002; Xiaodong Liu 004; Jie Yu 008; Shasha Li 001; Jun Ma 015; Xiaopeng Li 006; Shangwen Wang; Xinran Hong (CoRR, 2024)

Fusing Code Searchers. - Shangwen Wang; Mingyang Geng; Bo Lin; Zhensu Sun; Ming Wen 001; Yepang Liu 001; Li Li 029; Tegawendé F. Bissyandé; Xiaoguang Mao (IEEE Trans. Software Eng., 2024)

Model Editing for LLMs4Code: How Far are we? - Xiaopeng Li 006; Shangwen Wang; Shasha Li 001; Jun Ma 015; Jie Yu 008; Xiaodong Liu 004; Jing Wang; Bin Ji 002; Weimin Zhang (ICSE, 2025)

Instruct or Interact? Exploring and Eliciting LLMs' Capability in Code Snippet Adaptation Through Prompt Engineering. - Tanghaoran Zhang; Yue Yu 001; Xinjun Mao; Shangwen Wang; Kang Yang 001; Yao Lu 003; Zhang Zhang 005; Yuxin Zhao (ICSE, 2025)

Large Language Models Are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Tasks. - Kang Yang 001; Xinjun Mao; Shangwen Wang; Yanlin Wang 001; Tanghaoran Zhang; Bo Lin; Yihao Qin; Zhang Zhang 005; Yao Lu 003; Kamal Al-Sabahi (ICPC, 2025)

Improving API Knowledge Comprehensibility: A Context-Dependent Entity Detection and Context Completion Approach Using LLM. - Zhang Zhang 005; Xinjun Mao; Shangwen Wang; Kang Yang 001; Tanghaoran Zhang; Fei Gao; Xunhui Zhang (SANER, 2025)

Learning Feasible Causal Algorithmic Recourse: A Prior Structural Knowledge Free Approach. - Haotian Wang 001; Hao Zou 001; Xueguang Zhou; Shangwen Wang; Wenjing Yang 002; Peng Cui 001 (WWW, 2025)

GTE: learning code AST representation efficiently and effectively. - Yihao Qin; Shangwen Wang; Bo Lin; Kang Yang 001; Xiaoguang Mao (Sci. China Inf. Sci., 2025)

MiSum: Multi-modality Heterogeneous Code Graph Learning for Multi-intent Binary Code Summarization. - Kangchen Zhu; Zhiliang Tian; Shangwen Wang; Weiguo Chen; Zixuan Dong; Mingyue Leng; Xiaoguang Mao (Proc. ACM Softw. Eng., 2025)

Don't Complete It! Preventing Unhelpful Code Completion for Productive and Sustainable Neural Code Completion Systems. - Zhensu Sun; Xiaoning Du 001; Fu Song; Shangwen Wang; Mingze Ni; Li Li 029; David Lo 001 (ACM Trans. Softw. Eng. Methodol., 2025)

Exploring the Security Threats of Knowledge Base Poisoning in Retrieval-Augmented Code Generation. - Bo Lin; Shangwen Wang; Liqian Chen; Xiaoguang Mao (CoRR, 2025)

Mitigating Sensitive Information Leakage in LLMs4Code through Machine Unlearning. - Ruotong Geng; Mingyang Geng; Shangwen Wang; Haotian Wang 001; Zhipeng Lin; Dezun Dong (CoRR, 2025)

AutoRIC: Automated Neural Network Repairing Based on Constrained Optimization. - Xinyu Sun; Wanwei Liu; Shangwen Wang; Tingyu Chen; Ye Tao 008; Xiaoguang Mao (ACM Trans. Softw. Eng. Methodol., 2025)

Large Language Models-Aided Program Debloating. - Bo Lin; Shangwen Wang; Yihao Qin; Liqian Chen; Xiaoguang Mao (CoRR, 2025)

Smoke and Mirrors: Jailbreaking LLM-based Code Generation via Implicit Malicious Prompts. - Sheng Ouyang; Yihao Qin; Bo Lin; Liqian Chen; Xiaoguang Mao; Shangwen Wang (CoRR, 2025)

Divide-and-Conquer: Automating Code Revisions via Localization-and-Revision. - Shangwen Wang; Bo Lin; Liqian Chen; Xiaoguang Mao (ACM Trans. Softw. Eng. Methodol., 2025)

Give LLMs a Security Course: Securing Retrieval-Augmented Code Generation via Knowledge Injection. - Bo Lin; Shangwen Wang; Yihao Qin; Liqian Chen; Xiaoguang Mao (CoRR, 2025)

SoapFL: A Standard Operating Procedure for LLM-Based Method-Level Fault Localization. - Yihao Qin; Shangwen Wang; Yiling Lou; Jinhao Dong; Kaixin Wang; Xiaoling Li 002; Xiaoguang Mao (IEEE Trans. Software Eng., 2025)

Step More: Going Beyond Single Backpropagation in Meta Learning Based Model Editing. - Xiaopeng Li 006; Shasha Li 001; Xi Wang 018; Shezheng Song; Bin Ji 002; Shangwen Wang; Jun Ma 015; Xiaodong Liu 004; Mina Liu; Jie Yu 008 (CoRR, 2025)