I received my Ph.D. degree from National University of Defense Technology (NUDT) in 2026. During my Ph.D. study, I was fortunate to be supervised by Prof. Xinjun Mao and co-supervised by Prof. Yue Yu. I received the bachelor’s degree from Tsien Hsue-shen Class, NUDT, in June 2020. My research interests include AI4SE, code reuse, code snippet adaptation, and empirical software engineering. My papers have been published at top software engineering venues, including ICSE, FSE, ASE, ISSTA, TSE, TOSEM and EMSE, and have received 130+ citations on Google Scholar.

🔥 News

• 2026.09: 🎉🎉 Our paper about Logical Context Enhanced Code Generation (LogiCoder) was accepted by TOSEM after major revision! This is the final part of my Ph.D dissertation!
• 2026.07: 🎉🎉 Our paper about Block-aware Code Differencing was accepted by ASE 2026 after major revision! Congrats to Prof. Lu and Prof. Liu!
• 2026.05:  🎉🎉I have successfully defended my PhD dissertation!
• 2026.04:  🎉🎉 Our paper about Deprecated NPM Packages was directly accepted by ISSTA 2026 (10.1%)! This is the first ISSTA paper in our group! Congrats to Zezhou!
• 2025.12:  🎉🎉 Our paper about Context Adaptation Bug Resolution was directly accepted by FSE 2026 (9.4%)! This is the first FSE paper in our group!
• 2025.09:  🎉🎉 Our paper about Code Adaptation Benchmark (AdaptEval) was accepted by ASE 2025 after major revision! This is the first ASE paper in our group!
• 2025.04:  🎉🎉 Thrilled to announce our ICPC paper won 🏆ACM SIGSOFT Distinguished Paper Award!
• 2024.10:  🎉🎉 Our paper about LLM-based Code Adaptation was directly accepted by ICSE 2025 (10.3%)! This is the first CCF-A SE conference paper in our group!

📝 Publications

Representative Works

FSE 2026

Coding in a Bubble? Evaluating LLMs in Resolving Context Adaptation Bugs During Code Adaptation

Tanghaoran Zhang, Xinjun Mao, Shangwen Wang, Yuxin Zhao, Yao Lu, Zezhou Tang, Wenyu Xu, Longfei Sun, Changrong Xie, Kang Yang and Yue Yu.

FSE 2026 (CCF-A)

Project

• We propose CtxBugGen, a novel framework for generating CtxBugs through a four-step process: (1) Task Selection, (2) Syntax-based Perturbation, (3) LLM-based Variant Generation and (4) Hybrid Identification. Based on CtxBugGen, we reveal LLMs’ unsatisfactory performance in CtxBug resolution, highlighting their preference for local code correctness and critical weakness in cross-context reasoning.

TOSEM 2026

LLM See, LLM Do: Enhancing Repository-Aware Code Generation in LLMs Through Logical Context and Usage Knowledge

Tanghaoran Zhang, Xinjun Mao, Yuxin Zhao, Kang Yang, Zhang Zhang, Yao Lu, Youren Chen and Yue Yu.

TOSEM (CCF-A), 2026

Project

• We propose LogiCoder, a novel RAG approach that leverages logical relationships to improve LLMs’ repository awareness during code generation. Using a repository-level dependency graph, it retrieves candidate callees and their most contextually similar usage examples, then re-ranks them with semantic search results.

ASE 2025

AdaptEval: A Benchmark for Evaluating Large Language Models on Code Snippet Adaptation

Tanghaoran Zhang, Xinjun Mao, Shangwen Wang, Yuxin Zhao, Yao Lu, Jin Zhang, Zhang Zhang, Kang Yang and Yue Yu.

ASE 2025 (CCF-A)

Project | Video

• We construct AdaptEval, the first benchmark for evaluating LLM-based code snippet adaptation. It incorporates three distinctive features: (1) practical context derived from developers’ reuse practices; (2) multi-granularity annotations supporting evaluation across diverse adaptation scenarios; (3) fine-grained evaluation supporting evaluation across various individual adaptations.

ICSE 2025

Instruct or Interact? Exploring and Eliciting LLMs’ Capability in Code Snippet Adaptation Through Prompt Engineering

Tanghaoran Zhang, Yue Yu, Xinjun Mao, Shangwen Wang, Kang Yang, Yao Lu, Zhang Zhang and Yuxin Zhao.

ICSE 2025 (CCF-A)

Project

• We first empirically investigate the capability of LLMs on the code adaptation task and find the root causes of their sub-optimal performance: (1) Unclear Requirement, (2) Requirement Misalignment and (3) Context Misapplication. To resolve above issues, we propose an interactive prompting approach to eliciting LLMs’ ability in code snippet adaptation.

TSE 2024

How Do Developers Adapt Code Snippets to Their Contexts? An Empirical Study of Context-Based Code Snippet Adaptations

Tanghaoran Zhang, Yao Lu, Yue Yu, Xinjun Mao, Yang Zhang and Yuxin Zhao.

TSE (CCF-A), 2024

Project

• We investigate how developers adapt code snippets to their project context based on a semi-structured interview and a quantitative study on 300 real-world adaptation cases. We point out current challenges in the adaptation practices and obtain four typical context-based adaptation patterns.

• FENSE: A Feature-based Ensemble Modeling Approach to Cross-project Just-in-time Defect Prediction, Tanghaoran Zhang, Yue Yu, Xinjun Mao, Yao Lu, Zhixing Li and Huaimin Wang, EMSE (CCF-B, JCR-Q1), 2022

All Publications

• Detecting Evasive Benchmark Contamination in Code Generation by Mutating Code-Behavior Units, Menghan Wu, Xing Hu, Tanghaoran Zhang and Shanping Li, APSEC 2026 (CCF-C).
• BDiff: Block-aware and Accurate Text-based Code Differencing, Yao Lu, Wanwei Liu, Tanghaoran Zhang, Kang Yang, Yang Zhang, Wenyu Xu, Longfei Sun, Xinjun Mao, Shuzheng Gao and Michael R Lyu, ASE 2026 (CCF-A).
• Evaluating LLMs in ROS Robotic Software Code Generation, Yuxin Zhao, Xinjun Mao, Tanghaoran Zhang, Tun Li and Zhiqun Xiao, EMSE 2026 (CCF-B).
• Deprecated but Not Abandoned: A Large-Scale Empirical Study on Growing-user-demand Deprecated NPM Packages, Zezhou Tang, Yang Zhang, Xinjun Mao, Tanghaoran Zhang, Changrong Xie, Wenyu Xu, Simeng Yao and Yiwen Wu, ISSTA 2026 (CCF-A).
• ConflictLens: An LLM-Based Method for Detecting Semantic Merge Conflicts, Longfei Sun, Yao Lu, Xinjun Mao, Tanghaoran Zhang, Zhang Zhang and Huiping Zhou, SEKE 2025 (CCF-C).
• Understanding the Faults in Serverless Computing Based Applications: An Empirical Study, Changrong Xie, Yang Zhang, Xinjun Mao, Kang Yang and Tanghaoran Zhang, ICSME 2025 (CCF-B).
• CARLDA: An Approach for Stack Overflow API Mention Recognition Driven by Context and LLM-based Data Augmentation, Zhang Zhang, Xinjun Mao, Shangwen Wang, Kang Yang, Tanghaoran Zhang and Yao Lu, JSEP (CCF-B), 2025.
• Large Language Models are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Tasks, Kang Yang, Xinjun Mao, Shangwen Wang, Yanlin Wang, Tanghaoran Zhang, Bo Lin, Yihao Qin, Zhang Zhang, Yao Lu and Kamal Al-Sabahi, ICPC 2025 (CCF-B), 🏆ACM SIGSOFT Distinguished Paper Award.
• Improving API Knowledge Comprehensibility: A Context-Dependent Entity Detection and Context Completion Approach Using LLM, Zhang Zhang, Xinjun Mao, Shangwen Wang, Kang Yang, Tanghaoran Zhang, Fei Gao and Xunhui Zhang, SANER 2025 (CCF-B).
• An Empirical Study of Cross-Project Pull Request Recommendation in GitHub, Wenyu Xu, Yao Lu, Xunhui Zhang, Tanghaoran Zhang, Bo Lin and Xinjun Mao, APSEC 2024 (CCF-C).
• MUSE: A Multi-Feature Semantic Fusion Method for ROS Node Search Based on Knowledge Graph, Yuxin Zhao, Xinjun Mao, Tanghaoran Zhang and Zhang Zhang, APSEC 2023 (CCF-C).
• An Effective Method for Constructing Knowledge Graph to Search Reusable ROS Nodes, Yuxin Zhao, Xinjun Mao, Sun Bo, Tanghaoran Zhang and Shuo Yang, SEKE 2023 (CCF-C).
• An Extensive Study of the Structure Features in Transformer-based Code Semantic Summarization, Kang Yang, Xinjun Mao, Shangwen Wang, Yihao Qin, Tanghaoran Zhang, Yao Lu and Kamal Al-Sabahi, ICPC 2023 (CCF-B).
• Verifying ReLU Neural Networks from a Model Checking Perspective, Wanwei Liu, Fu Song, Tanghaoran Zhang and Ji Wang, JCST (CCF-B), 2020.

🎖 Honors and Awards

• 2025.11, 💰First-Prize Merit Scholarship, NUDT.
• 2025.04, 🏆ACM SIGSOFT Distinguished Paper Award in ICPC 2025.
• 2023.03, 💰Second-Prize Merit Scholarship, NUDT.
• 2020.05, 💰Qiangjun Scholarship, NUDT.
• 2019.10, 🏅Outstanding Winner of M* Modeling Contest.
• 2019.10, 🏆CCF Outstanding Undergraduate, CCF.
• 2019.05, 💰Yinhe Scholarship, College of Computer Science and Technology, NUDT.
• 2019.05, 🏅Meritorious Winner of MCM/ICM.
• 2018.05, 🏅Meritorious Winner of MCM/ICM.

📖 Educations

• 2020.09 - 2026.06, National University of Defense Technology (NUDT), Ph.D. in Software Engineering.
• 2016.09 - 2020.06, Tsien Hsue-shen Class (1/30), National University of Defense Technology (NUDT), B.E. in Software Engineering.
• 2010.09 - 2016.06, The High School Affiliated to Renmin University of China (RDFZ), Middle and High School.

⚙️ Services

• Program Committee
  • ICSE’26 Shadow PC
• Reviewer
  • TSE, EMSE, KAIS
• External Reviewer
  • Journal: TSE, TOSEM, EMSE, JCST, JoS
  • Conference: FSE’26, SANER’26, ICLR’25, ASE’24, ESEM’24

💬 Invited Talks

• 2026.04, FSE 2026 Paper Pre-conference Presentation | Video.
• 2025.11, ASE 2025 Paper Pre-conference Presentation | Video.
• 2024.12, ICSE 2025 Paper Pre-conference Presentation | Video.

💻 Internships

• 2025.03 - 2025.10, Visiting student at Peng Cheng Laboratory, Shenzhen, Guangdong.
• 2019.07 - 2019.10, Mitacs Research Internship, at SEAL in Queen’s University, Canada, supervised by Prof. Ying Zou.