📌 Publications

• [arXiv] A Survey of Reinforcement Learning for Software Engineering.
  Dong Wang, Hanmo You, Lingwei Zhu, Kaiwei Lin, Zheng Chen, Chen Yang, Junji Yu, Zan Wang, Junjie Chen.
• [arXiv] Issue-Oriented Agent-Based Framework for Automated Review Comment Generation.
  Shuochuan Li, Dong Wang*, Patanamon Thongtanunam, Zan Wang, Jiuqiao Yu, Junjie Chen.
• [arXiv] On the Effectiveness of Training Data Optimization for LLM-based Code Generation: An Empirical Study.
  Shiqi Kuang, Zhao Tian, Tao Xiao, Dong Wang, Junjie Chen.
• [arXiv] Large Language Models for Multilingual Vulnerability Detection: How Far Are We?.
  Honglin Shu, Michael Fu, Junji Yu, Dong Wang*, Chakkrit Tantithamthavorn, Yasutaka Kamei, Junjie Chen.
• [arXiv] FLAME: Enhancing Functional Coverage in Processor Verification via Large Language Models.
  Xiaopeng Li, Junjie Chen, Ming Yan, Dong Wang, Xingyu Fan, Zhentao Tang, Shixiong Kai, Jianye Hao, Mingxuan Yuan, Zan Wang.
• [FSE’26] Characterizing and Mitigating False-Positive Bug Reports in the Linux Kernel.
  Jiashuo Tian, Dong Wang*, Chen Yang, Haichi Wang, Zan Wang, Junjie Chen. The ACM International Conference on the Foundations of Software Engineering.
• [ICSE’26] WiseUT: An Intelligent Framework for Unit Test Generation.
  Chen Yang, Ziqi Wang, Lin Yang, Dong Wang, Shutao Gao, Yanjie Jiang, Junjie Chen. The 48th International Conference on Software Engineering, Demos.
• [ICSE’25] Selecting Initial Seeds for Better JVM Fuzzing.
  Tianchang Gao, Junjie Chen, Dong Wang, Yile Guo, Yingquan Zhao, Zan Wang. The 47th IEEE/ACM International Conference on Software Engineering.
• [ASE’25] Clarifying Semantics of In-Context Examples for Unit Test Generation.🏆[Distinguished Paper Award]
  Chen Yang, Lin Yang, Ziqi Wang, Dong Wang, Jianyi Zhou, Junjie Chen. 40th IEEE/ACM International Conference on Automated Software Engineering.
• [TOSEM’25] On the Evaluation of Large Language Models in Multilingual Vulnerability Repair.
  Dong Wang, Junji Yu, Honglin Shu, Michael Fu, Chakkrit Tantithamthavorn, Junjie Chen, Yasutaka Kamei. ACM Transactions on Software Engineering and Methodology.
• [TOSEM’25] An Empirical Study on Language Models for Generating Log Statements in Test Code.
  Honlin Shu, Dong Wang*, Antonio Mastropaolo, Gabriele Bavota, Yasutaka Kamei. ACM Transactions on Software Engineering and Methodology.
• [TOSEM’25] False-Positive Bug Reports in Deep Learning Compilers: Stages, Root Causes, and Mitigation.
  Huang, Lili, Shen, Qingchao, Dong Wang*, Wu, Yunping, Wang, Meng, Chen, Junjie. ACM Transactions on Software Engineering and Methodology.
• [TOSEM’25] LEAM++: Learning for Selective Mutation Fault Construction.
  Zhao Tian, Junjie Chen, Dong Wang*, Qihao Zhu, Xingyu Fan, Lingming Zhang. ACM Transactions on Software Engineering and Methodology.
• [EMSE’25] Developer Reactions to Protestware in Open Source Software: The cases of color.js and es5.ext.
  Youmei Fan, Dong Wang*, Supatsara Wattanakriengkrai, Hathaichanok Damrongsiri, Christoph Treude, Hideaki Hata, Raula Gaikovina Kula. Empirical Software Engineering.
• [ASEJ’25] An Empirical Study of Test Case Prioritization on the Linux Kernel.
  Haichi Wang, Ruiguo Yu, Dong Wang, Yiheng Du, Yingquan Zhao, Junjie Chen, Zan Wang. Automated Software Engineering Journal.
• [ISSTA’25 - Workshop] A Preliminary Study of Large Language Models for Multilingual Vulnerability Detection.
  Junji Yu, Honglin Shu, Michael Fu, Dong Wang*, Chakkrit Tantithamthavorn, Yasutaka Kamei, Junjie Chen. The 1st International Workshop on Large Language Model Supply Chain Analysis.
• [ISSTA’24] Large Language Models for Equivalent Mutant Detection: How Far are We?.🏆[Distinguished Paper Award]
  Zhao Tian, Honglin Shu, Dong Wang*, Xuejie Cao, Yasutaka Kamei, Junjie Chen. 33rd International Symposium on Software Testing and Analysis.
• [TOSEM’24] A Disruptive Research Playbook for Studying Disruptive Innovations.
  Margaret-Anne Storey, Daniel Russo, Nicole Novielli, Takashi Kobayashi, Dong Wang. ACM Transactions on Software Engineering and Methodology.
• [ICSME’24] Towards Identifying Python Proficiency to Foster Software Maintenance and Evolution.
  Ruksit Rojpaisarnkit, Gregorio Robles, Raula Gaikovina Kula, Dong Wang, Chaiyong Ragkhitwetsagul, Jesus M. Gonzalez-Barahona, Kenichi Matsumoto. 40th IEEE International Conference on Software Maintenance and Evolution.
• [EMSE’24] Understanding the Characteristics and the Role of Visual Issue Reports.
  Hiroki Kuramoto, Dong Wang*, Masanari Kondo, Yutaro Kashiwa, Yasutaka Kamei, Naoyasu Ubayashi. Empirical Software Engineering.
• [EMSE’24] Quantifying and Characterizing Clones of Self-Admitted Technical Debt in Build Systems.
  Tao Xiao, Zhili Zeng, Dong Wang*, Hideaki Hata, Shane McIntosh, Kenichi Matsumoto. Empirical Software Engineering.
• [MSR’24] Exploring the Effect of Multiple Natural Languages on Code Suggestion Using GitHub Copilot.
  Kei Koyanagi, Dong Wang, Kotaro Noguchi, Masanari Kondo, Alexander Serebrenik, Yasutaka Kamei, Naoyasu Ubayashi. 21th IEEE International Conference on Mining Software Repositories.
• [SCAM’24] GitRev: An LLM-based Gamification Framework for Modern Code Review Activities.
  Jasem Khelifi, Moataz Chouchen, Ali Ouni, Raula Gaikovina Kula, Dong Wang, Salma Hamza, and Mohamed Wiem Mkaouer. 24th IEEE International Conference on Source Code Analysis and Manipulation.
• [ASE’23] Unjustifiable Waste: An Empirical Study of Repeated Builds During Code Review.
  Rungroj Maipradit, Dong Wang*, Patanamon Thongtanunam, Raula Gaikovina Kula, Yasutaka Kamei, Shane McIntosh. 38th IEEE/ACM International Conference on Automated Software Engineering.
• [EMSE’23] When Conversations Turn Into Work: A Taxonomy of Converted Discussions and Issues in GitHub.
  Dong Wang, Masanari Kondo, Yasutaka Kamei, Raula Gaikovina Kula, Naoyasu Ubayashi. Empirical Software Engineering.
• [EMSE’23] More Than React: Investigating The Role of Emoji Reaction in GitHub Pull Requests.
  Dong Wang, Tao Xiao, Teyon Son, Raula Gaikovina Kula, Takashi Ishio, Yasutaka Kamei, Kenichi Matsumoto. Empirical Software Engineering.
• [MSR’23] Understanding the Role of Images on Stack Overflow.
  Dong Wang, Tao Xiao, Christoph Treude, Raula Gaikovina Kula, Hideaki Hata, Yasutaka Kamei. 20th IEEE International Conference on Mining Software Repositories.
• [SANER’23] Towards Privacy Preserving Cross Project Defect Prediction with Federated Learning.
  Hiroki Yamamoto, Dong Wang*, Gopi Rajbahadur, Masanari Kondo, Yasutaka Kamei, Naoyasu Ubayashi. 30th IEEE International Conference on Software Analysis, Evolution and Reengineering.
• [TSE’22] Giving Back: Contributions Congruent to Library Dependency Changes in a Software Ecosystem.
  Supatsara Wattanakriengkrai, Dong Wang, Raula Gaikovina Kula, Christoph Treude, Patanamon Thongtanunam, Takashi Ishio, Kenichi Matsumoto. IEEE Transactions on Software Engineering.
• [TSE’22] Characterizing and Mitigating Self-Admitted Technical Debt in Build Systems.
  Tao Xiao, Dong Wang, Shane McIntosh, Hideaki Hata, Raula Gaikovina Kula, Takashi Ishio, Kenichi Matsumoto. IEEE Transactions on Software Engineering.
• [EMSE’22] Newcomer Candidate: Characterizing Contributions of a Novice Developer to GitHub.
  Ifraz Rehman, Dong Wang, Raula Gaikovina Kula, Takashi Ishio, Kenichi Matsumoto. Empirical Software Engineering.
• [EMSE’21] Understanding Shared Links and Their Intentions to Meet Information Needs in Modern Code Review.
  Dong Wang, Tao Xiao, Patanamon Thongtanunam, Raula Gaikovina Kula, Kenichi Matsumoto. Empirical Software Engineering.
• [JSS’21] Can We Benchmark Code Review Studies? A Systematic MappingStudy of Methodology, Dataset, and Metric?.
  Dong Wang, Yuki Ueda, Raula Gaikovina Kula, Takashi Ishio, Kenichi Matsumoto. Journal of Systems and Software.
• [IST’21] Automatic Patch Linkage Detection in Code Review Using Textual Content and File Location Features.
  Dong Wang, Raula Gaikovina Kula, Takashi Ishio, Kenichi Matsumoto. Information and Software Technology.
• [SANER’21] Anti-patterns in Modern Code Review: Symptoms and Prevalence.
  Moataz Chouchen, Ali Ouni, Raula Gaikovina Kula, Dong Wang, Patanamon Thongtanunam, Mohamed Wiem Mkaouer, Kenichi Matsumoto. 28th IEEE International Conference on Software Analysis, Evolution and Reengineering.
• [IWESEP’19] How Do Contributors Impact Code Naturalness? An Exploratory Study of 50 Python Projects.
  Thanadon Bunkerd, Dong Wang, Raula Gaikovina Kula, Chaiyong Ragkhitwetsagul, Morakot Choetkiertikul, Thanwadee Sunetnanta, Takashi Ishio, Kenichi Matsumoto. 10th International Workshop on Empirical Software Engineering in Practice.
• [IWESEP’19] Visualizing the Usage of Pythonic Idioms Over Time: A Case Study of the with open Idiom.
  Tattiya Sakulniwat, Raula Gaikovina Kula, Chaiyong Ragkhitwetsagul, Morakot Choetkiertikul, Thanwadee Sunetnanta, Dong Wang, Takashi Ishio, Kenichi Matsumoto. 10th International Workshop on Empirical Software Engineering in Practice.