The Design of a Flexible Software Process Language. - Beijun Shen; Cheng Chen (SPW/ProSim, 2006)

On the Measurement of Agility in Software Process. - Beijun Shen; Dehua Ju (ICSP, 2007)

A Case Study of Software Process Improvement in a Chinese Small Company. - Beijun Shen; Tong Ruan (CSSE (2), 2008)

Support IT Service Management with Process Modeling and Analysis. - Beijun Shen (ICSP, 2008)

Extending Model Driven Architecture with Software Security Assessment. - Xucheng Tang; Beijun Shen (SSIRI, 2009)

IT Service Support Process Meta-Modeling Based on ITIL. - Xin Huang; Beijun Shen; Delai Chen (DSDE, 2010)

Enhance Information Flow Tracking with Function Recognition. - Kan Zhou; Shiqiu Huang; Zhengwei Qi; Jian Gu; Beijun Shen (e-Forensics, 2010)

Engineering Adaptive IT Service Support Processes Using Meta-modeling Technologies. - Beijun Shen; Xin Huang; Kai Zhou; Wenwei Tang (ICSP, 2010)

On Knowledge Services for Outsourcing Professional Development. - Dehua Ju; Beijun Shen (SEAFOOD, 2010)

Knowledge Services for Knowledge Workers. - Dehua Ju; Beijun Shen (WSKS (1), 2010)

Measuring and Improving IT Service Support Processes: A Case Study. - Kai Zhou; Beijun Shen (EAST, 2011)

A semantic unification approach for M2M applications based on ontology. - Menghan Chen; Beijun Shen (WiMob, 2011)

Compressed C4.5 Models for Software Defect Prediction. - Jun Wang; Beijun Shen; Yuting Chen 001 (QSIC, 2012)

Towards Agile Application Integration with M2M Platforms. - Menghan Chen; Beijun Shen (KSII Trans. Internet Inf. Syst., 2012)

Mining GitHub: Why Commit Stops - Exploring the Relationship between Developer's Commit Pattern and File Version Evolution. - Weicheng Yang; Beijun Shen; Ben Xu (APSEC (2), 2013)

Mining Developer Mailing List to Predict Software Defects. - Yu Zhang; Beijun Shen; Yuting Chen 001 (APSEC (1), 2014)

A Scenario-Based Approach to Predicting Software Defects Using Compressed C4.5 Model. - Biwen Li; Beijun Shen; Jun Wang; Yuting Chen 001; Tao Zhang; Jinshuang Wang (COMPSAC, 2014)

TBIL: A Tagging-Based Approach to Identity Linkage Across Software Communities. - Wenkai Mo; Beijun Shen; Yuting Chen 001; Jiangang Zhu (APSEC, 2015)

A Learning to Rank Framework for Developer Recommendation in Software Crowdsourcing. - Jiangang Zhu; Beijun Shen; Fanghuai Hu (APSEC, 2015)

Code Bad Smell Detection through Evolutionary Data Mining. - Shizhe Fu; Beijun Shen (ESEM, 2015)

GEMiner: Mining Social and Programming Behaviors to Identify Experts in Github. - Wenkai Mo; Beijun Shen; Yuming He; Hao Zhong 001 (Internetware, 2015)

Cross-Project Software Defect Prediction Using Feature-Based Transfer Learning. - He Qing; Biwen Li; Beijun Shen; Yong Xia 009 (Internetware, 2015)

Towards Effective Developer Recommendation in Software Crowdsourcing. - Shixiong Zhao; Beijun Shen; Yuting Chen 001; Hao Zhong 001 (SEKE, 2015)

Building a Large-scale Software Programming Taxonomy from Stackoverflow. - Jiangang Zhu; Beijun Shen; Xuyang Cai; Haofen Wang (SEKE, 2015)

Software.zhishi.schema: A Software Programming Taxonomy Derived from Stackoverflow. - Jiangang Zhu; Haofen Wang; Beijun Shen (ISWC (Posters & Demos), 2015)

Task Recommendation with Developer Social Network in Software Crowdsourcing. - Ning Li; Wenkai Mo; Beijun Shen (APSEC, 2016)

EXPSOL: Recommending Online Threads for Exception-Related Bug Reports. - Xiaoning Liu; Beijun Shen; Hao Zhong 001; Jiangang Zhu (APSEC, 2016)

Heterogeneous Cross-Company Effort Estimation through Transfer Learning. - Shensi Tong; Qing He; Yuting Chen 001; Ye Yang; Beijun Shen (APSEC, 2016)

GRETA: Graph-Based Tag Assignment for GitHub Repositories. - Xuyang Cai; Jiangang Zhu; Beijun Shen; Yuting Chen 001 (COMPSAC, 2016)

Software Defect Prediction Using Semi-Supervised Learning with Change Burst Information. - Qing He; Beijun Shen; Yuting Chen 001 (COMPSAC, 2016)

SOLinker: Constructing Semantic Links between Tags and URLs on StackOverflow. - Wenkai Mo; Jiangang Zhu; Zhenzheng Qian; Beijun Shen (COMPSAC, 2016)

SatiIndicator: Leveraging User Reviews to Evaluate User Satisfaction of SourceForge Projects. - Zhenzheng Qian; Beijun Shen; Wenkai Mo; Yuting Chen 001 (COMPSAC, 2016)

ESSE: an early software size estimation method based on auto-extracted requirements features. - Cheng Zhang; Shensi Tong; Wenkai Mo; Yang Zhou; Yong Xia 009; Beijun Shen (Internetware, 2016)

Building a Domain Knowledge Base from Wikipedia: a Semi-supervised Approach. - Kai Chen; Xiang Dong; Jiangang Zhu; Beijun Shen (SEKE, 2016)

Learning to Discover Subsumptions between Software Engineering Concepts in Wikipedia. - Xiang Dong; Kai Chen; Jiangang Zhu; Beijun Shen (SEKE, 2016)

CPDScorer: Modeling and Evaluating Developer Programming Ability across Software Communities. - Weizhi Huang; Wenkai Mo; Beijun Shen; Yu Yang; Ning Li (SEKE, 2016)

Operational pattern based code generation for management information system: An industrial case study. - Fagui Mao; Xuyang Cai; Beijun Shen; Yong Xia 009; Bo Jin (SNPD, 2016)

Automatically Modeling Developer Programming Ability and Interest Across Software Communities. - Weizhi Huang; Wenkai Mo; Beijun Shen; Yu Yang; Ning Li (Int. J. Softw. Eng. Knowl. Eng., 2016)

Transfer Learning for Cross-Platform Software Crowdsourcing Recommendation. - Shuhan Yan; Beijun Shen; Wenkai Mo; Ning Li (APSEC, 2017)

How Do Programmers Maintain Concurrent Code? - Feiyue Yu; Hao Zhong 001; Beijun Shen (APSEC, 2017)

CRSearcher: Searching Code Database for Repairing Bugs. - Yingyi Wang; Yuting Chen 001; Beijun Shen; Hao Zhong 001 (Internetware, 2017)

A GQM-based Approach for Software Process Patterns Recommendation. - Zhangyuan Meng; Cheng Zhang; Beijun Shen; Yin Wei (SEKE, 2017)

Mining Developer Behavior Across GitHub and StackOverflow. - Yunxiang Xiong; Zhangyuan Meng; Beijun Shen; Wei Yin (SEKE, 2017)

Cold-Start Developer Recommendation in Software Crowdsourcing: A Topic Sampling Approach. - Yu Yang; Wenkai Mo; Beijun Shen; Yuting Chen 001 (SEKE, 2017)

Developer Identity Linkage and Behavior Mining Across GitHub and StackOverflow. - Yunxiang Xiong; Zhangyuan Meng; Beijun Shen; Wei Yin (Int. J. Softw. Eng. Knowl. Eng., 2017)

SLAMPA: Recommending Code Snippets with Statistical Language Model. - Shufan Zhou; Hao Zhong 001; Beijun Shen (APSEC, 2018)

Reinforcement Learning of Code Search Sessions. - Wei Li 254; Shuhan Yan; Beijun Shen; Yuting Chen 001 (APSEC, 2019)

An Adaptive Approach to Recommending Obfuscation Rules for Java Bytecode Obfuscators. - Yanru Peng; Yuting Chen 001; Beijun Shen (COMPSAC (1), 2019)

CocoQa: Question Answering for Coding Conventions Over Knowledge Graphs. - Tianjiao Du; Junming Cao; Qinyue Wu; Wei Li 254; Beijun Shen; Yuting Chen 001 (ASE, 2019)

Lancer: Your Code Tell Me What You Need. - Shufan Zhou; Beijun Shen; Hao Zhong 001 (ASE, 2019)

Constructing a Knowledge Base of Coding Conventions from Online Resources. - Junming Cao; Tianjiao Du; Beijun Shen; Wei Li 254; Qinyue Wu; Yuting Chen 001 (SEKE, 2019)

Generating SQL Statements from Natural Language Queries: A Multitask Learning Approach (S). - Chunqi Chen; Yunxiang Xiong; Beijun Shen; Yuting Chen 001 (SEKE, 2019)

Enhancing Semantic Search of Crowdsourcing IT Services using Knowledge Graph. - Duankang Fu; Shufan Zhou; Beijun Shen; Yuting Chen 001 (SEKE, 2019)

CrowDevBot: A Task-Oriented Conversational Bot for Software Crowdsourcing Platform (S). - Zeyu Ni; Beijun Shen; Yuting Chen 001; Zhangyuan Meng; Junming Cao (SEKE, 2019)

Learning Code-Query Interaction for Enhancing Code Searches. - Wei Li 254; Haozhe Qin; Shuhan Yan; Beijun Shen; Yuting Chen 001 (ICSME, 2020)

Learning to Recommend Trigger-Action Rules for End-User Development - A Knowledge Graph Based Approach. - Qinyue Wu; Beijun Shen; Yuting Chen 001 (ICSR, 2020)

BugPecker: Locating Faulty Methods with Deep Learning on Revision Graphs. - Junming Cao; Shouliang Yang; Wenhui Jiang; Hushuang Zeng; Beijun Shen; Hao Zhong 001 (ASE, 2020)

Are the Code Snippets What We Are Searching for? A Benchmark and an Empirical Study on Code Search with Natural-Language Queries. - Shuhan Yan; Hang Yu; Yuting Chen 001; Beijun Shen; Lingxiao Jiang (SANER, 2020)

Semantic Service Search in IT Crowdsourcing Platform: A Knowledge Graph-Based Approach. - Qinyue Wu; Duankang Fu; Beijun Shen; Yuting Chen 001 (Int. J. Softw. Eng. Knowl. Eng., 2020)

Feedback2Code: A Deep Learning Approach to Identifying User-Feedback-Related Source Code Files. - Shuhan Yan; Tianjiao Du; Beijun Shen; Yuting Chen 001; Zhilei Ren (Int. J. Softw. Eng. Knowl. Eng., 2020)

Mining API Constraints from Library and Client to Detect API Misuses. - Hushuang Zeng; Jingxin Chen; Beijun Shen; Hao Zhong 001 (APSEC, 2021)

Learning to Match Workers and Tasks via a Multi-View Graph Attention Network. - Nan Cui; Chunqi Chen; Beijun Shen; Yuting Chen 001 (COMPSAC, 2021)

ApproxiFuzzer: Fuzzing towards Deep Code Snippets in Java Programs. - Xintian Yu; Enze Ma; Pengbo Nie; Beijun Shen; Yuting Chen 001; Ziyi Lin (COMPSAC, 2021)

Tensfa: Detecting and Repairing Tensor Shape Faults in Deep Learning Systems. - Dangwei Wu; Beijun Shen; Yuting Chen 001; He Jiang 001; Lei Qiao 002 (ISSRE, 2021)

Locating Faulty Methods with a Mixed RNN and Attention Model. - Shouliang Yang; Junming Cao; Hushuang Zeng; Beijun Shen; Hao Zhong 001 (ICPC, 2021)

ConLAR: Learning to Allocate Resources to Docker Containers under Time-Varying Workloads. - Diwei Chen; Beijun Shen; Yuting Chen 001 (QRS, 2021)

Weakly-Supervised Question Answering with Effective Rank and Weighted Loss over Candidates. - Haozhe Qin; Jiangang Zhu; Beijun Shen (WWW, 2021)

An Empirical Study on Tensor Shape Faults in Deep Learning Systems. - Dangwei Wu; Beijun Shen; Yuting Chen 001 (CoRR, 2021)

Context-Aware Conversational Recommendation of Trigger-Action Rules in IoT Programming. - Mingxin Zhao; Qinyue Wu; Enze Ma; Beijun Shen; Yuting Chen 001 (Int. J. Softw. Eng. Knowl. Eng., 2021)

DeFiHap: Detecting and Fixing HiveQL Anti-Patterns. - Yuetian Mao; Shuai Yuan; Nan Cui; Tianjiao Du; Beijun Shen; Yuting Chen 001 (Proc. VLDB Endow., 2021)

Code Question Answering via Task-Adaptive Sequence-to-Sequence Pre-training. - Tingrui Yu; Xiaodong Gu 002; Beijun Shen (APSEC, 2022)

Cross-Domain Deep Code Search with Meta Learning. - Yitian Chai; Hongyu Zhang 002; Beijun Shen; Xiaodong Gu 002 (ICSE, 2022)

Zero-shot program representation learning. - Nan Cui; Yuze Jiang; Xiaodong Gu 002; Beijun Shen (ICPC, 2022)

Self-supervised learning of smart contract representations. - Shouliang Yang; Xiaodong Gu 002; Beijun Shen (ICPC, 2022)

Answering Software Deployment Questions via Neural Machine Reading at Scale. - Guanjie Qiu; Diwei Chen; Shuai Zhang; Yitian Chai; Xiaodong Gu 002; Beijun Shen (ASE, 2022)

Diet code is healthy: simplifying programs for pre-trained models of code. - Zhaowei Zhang; Hongyu Zhang 002; Beijun Shen; Xiaodong Gu 002 (ESEC/SIGSOFT FSE, 2022)

Cross-Domain Deep Code Search with Few-Shot Meta Learning. - Yitian Chai; Hongyu Zhang 002; Beijun Shen; Xiaodong Gu 002 (CoRR, 2022)

Clean and Learn: Improving Robustness to Spurious Solutions in API Question Answering. - Shuai Yuan; Haozhe Qin; Xiaodong Gu 002; Beijun Shen (Int. J. Softw. Eng. Knowl. Eng., 2022)

Automatically repairing tensor shape faults in deep learning programs. - Dangwei Wu; Beijun Shen; Yuting Chen 001; He Jiang 001; Lei Qiao 002 (Inf. Softw. Technol., 2022)

Lejacon: A Lightweight and Efficient Approach to Java Confidential Computing on SGX. - Xinyuan Miao; Ziyi Lin; Shaojun Wang; Lei Yu; Sanhong Li; Zihan Wang; Pengbo Nie; Yuting Chen 001; Beijun Shen; He Jiang 001 (ICSE, 2023)

On the Evaluation of Neural Code Translation: Taxonomy and Benchmark. - Mingsheng Jiao; Tingrui Yu; Xuan Li; Guanjie Qiu; Xiaodong Gu 002; Beijun Shen (ASE, 2023)

InfeRE: Step-by-Step Regex Generation via Chain of Inference. - Shuai Zhang; Xiaodong Gu 002; Yuting Chen 001; Beijun Shen (ASE, 2023)

DuReSE: Rewriting Incomplete Utterances via Neural Sequence Editing. - Wenhui Jiang; Xiaodong Gu 002; Yuting Chen 001; Beijun Shen (Neural Process. Lett., 2023)

Unraveling the Potential of Large Language Models in Code Translation: How Far are We? - Qingxiao Tao; Tingrui Yu; Xiaodong Gu 002; Beijun Shen (APSEC, 2024)

Zero-Shot Code Representation Learning via Prompt Tuning. - Nan Cui; Xiaodong Gu 002; Beijun Shen (CoRR, 2024)

Few-shot code translation via task-adapted prompt learning. - Xuan Li; Shuai Yuan; Xiaodong Gu 002; Yuting Chen 001; Beijun Shen (J. Syst. Softw., 2024)

Project-specific code summarization with in-context learning. - Shangbo Yun; Shuhuai Lin; Xiaodong Gu 002; Beijun Shen (J. Syst. Softw., 2024)

ApiRAT: Integrating Multi-source API Knowledge for Enhanced Code Translation with LLMs. - Chaofan Wang; Guanjie Qiu; Xiaodong Gu 002; Beijun Shen (COMPSAC, 2025)

Empowering AI to Generate Better AI Code: Guided Generation of Deep Learning Projects with LLMs. - Chen Xie; Mingsheng Jiao; Xiaodong Gu 002; Beijun Shen (COMPSAC, 2025)

Just-in-time software defect prediction via bi-modal change representation learning. - Yuze Jiang; Beijun Shen; Xiaodong Gu 002 (J. Syst. Softw., 2025)

Anti-adversarial Learning: Desensitizing Prompts for Large Language Models. - Xuan Li; Zhe Yin; Xiaodong Gu 002; Beijun Shen (CoRR, 2025)

EVOC2RUST: A Skeleton-guided Framework for Project-Level C-to-Rust Translation. - Chaofan Wang; Tingrui Yu; Jie Wang; Dong Chen; Wenrui Zhang; Yuling Shi; Xiaodong Gu 002; Beijun Shen (CoRR, 2025)

Transplant Then Regenerate: A New Paradigm for Text Data Augmentation. - Guangzhan Wang; Hongyu Zhang 002; Beijun Shen; Xiaodong Gu 002 (CoRR, 2025)