Feifei Niu' Home Page

Feifei Niu

Research Fellow at Nanda Lab, University of Ottawa, with Prof. Lionel C. Briand.

I received my Ph.D. in Software Engineering from Nanjing University in 2023, co-supervised by Prof. Bin Luo, Prof. Jidong Ge, and Dr. Chuanyi Li. I was very fortunate to have the opportunity to work with Prof. Alexander Egyed, Prof. Liguo Huang, Prof. Wesley K. G. Assunção, and Dr. Christoph Mayr-Dorn on refactoring-based bug localization and defect prediction research. In 2018, I received my B.S. in Software Engineering from Tianjin University.

Email: feifeiniu96 AT gmail.com OR fniu2 AT uottawa.ca

Publications (* Corresponding author)

2025

[CSUR] Feifei Niu, Chuanyi Li, Kui Liu, Xin Xia, David Lo: “When Deep Learning Meeting Information Retrieval-based Bug Localization: A Survey”, in ACM Computing Surveys, 2025.🔗

[Internetware] Haosheng Zuo, Feifei Niu, Chuanyi Li: “Enhancement Report Approval Prediction: A Comparative Study of Large Language Models”, in 16th International Conference on Internetware, 2025.🔗

[arXiv] Feifei Niu, Rongqi Pan, Lionel C Briand, Hanyang Hu, Krishna Koravadi: “TVR: Automotive System Requirement Traceability Validation and Recovery Through Retrieval-Augmented Generation”, 2025.🔗

[arXiv] Xing Hu, Feifei Niu*, Junkai Chen, Xin Zhou, Junwei Zhang, Junda He, Xin Xia, David Lo: “Assessing and Advancing Benchmarks for Evaluating Large Language Models in Software Engineering Tasks”, 2025. 🔗

2024

[EMSE] Feifei Niu*, Enshuo Zhang, Christoph Mayr-Dorn, Wesley K. G. Assunçao, LiGuo Huang, Jidong Ge, Bin Luo, Alexander Egyed: “An Extensive Replication Study of the ABLoTS Approach for Bug Localization”, in Empirical Software Engineering, 29(6), 143, 2024.🔗

[ASE] Xiao Yu, Zexian Zhang, Feifei Niu*, Xing Hu, Xin Xia, John Grundy: “What Makes a High-Quality Training Dataset for Large Language Models: A Practitioners’ Perspective”, in 39th International Conference on Automated Software Engineering, 2024.🔗

[ICSE Demo] Feifei Niu, Junqian Shao, Chaofan Xu, Christoph Mayr-Dorn, Wesley Assunção, Liguo Huang, Chuanyi Li, Jidong Ge, Bin Luo, Alexander Egyed: “RAT: A Refactoring-Aware Tool for Tracking Code History”, in 46th International Conference on Software Engineering (Demonstration), 2024. 🔗

[Journal of Software] Zongwen Shen, Feifei Niu, Chuanyi Li, Xiang Chen, Qi Li, Jidong Ge, Bin Luo: “Two-Stage Bug Location Method Combining Information Retrieval and Deep Model Features”, Journal of Software (in Chinese), 2024. 🔗

2023

[ICSE] Feifei Niu, Wesley K. G. Assunçao, LiGuo Huang, Christoph Mayr-Dorn, Jidong Ge, Bin Luo, Alexander Egyed: “RAT: A Refactoring-Aware Traceability Model for Bug Localization”, in 45th International Conference on Software Engineering, 2023. 🔗

[MSR 🏆] Feifei Niu, Christoph Mayr-Dorn, Wesley K. G. Assunçao, LiGuo Huang, Jidong Ge, Bin Luo, Alexander Egyed: “The ABLoTS Approach for Bug Localization: is it replicable and generalizable?”, in 20th International Conference on Mining Software Repositories, ACM Distinguished Paper Award, 2023. 🔗

[Journal of Software] Feifei Niu, Chuanyi Li, Jidong Ge, Bin Luo: “Survey on User Feature Requests Analysis and Processing”, Journal of Software (in Chinese), 2023. 🔗

2022

[TSC] Feifei Niu, Chuanyi Li, Jidong Ge, Lijie Wen, Zhongjin Li, Bin Luo: “Measuring Business Process Behavioral Similarity Based on Token Log Profile”, in IEEE Transactions on Services Computing (2022) pp. 3344–3357. IEEE, 2022. 🔗

[Internetware] Feifei Niu, Chuanyi Li, Heng Chen, Jidong Ge, Bin Luo: “Towards Just-In-Time Feature Request Approval Prediction”, in 13th Asia Pacific Symposium on Internetware, 2022. 🔗

2021

[IIoTBDSC] Feifei Niu, Chuanyi Li, Bin Luo: “A Deep Classifier for Crowdsourcing User Requests”, in Modern Industrial IoT, Big Data and Supply Chain, 2021. 🔗

Patents

Chuanyi Li, Feifei Niu, Jidong Ge. A Token Log based Business Process Model Similarity Measurement. (202110045604.8) (In Chinese)

Chuanyi Li, Jidong Ge, Feifei Niu, Xiaoyu Zhou, Bin Luo. A Framework for Crowdsourcing Software Assets Management and Analysis. (201911048873.9)(In Chinese)

Tools

RAT is a refactoring-aware traceability tool for code history. Welcome to come up with more requests~

Services

2nd AI Foundation Models and Software Engineering (FORGE 2025): Local Arrangements Co-Chair & Social Media Co-Chair
45th IEEE/ACM International Conference on Software Engineering (ICSE 2023) - student volunteer

Program Committee

48th International Conference on Software Engineering (ICSE 2026) - Research Track
40th IEEE/ACM International Conference on Automated Software Engineering (ASE 2025) - Research Track
40th IEEE/ACM International Conference on Automated Software Engineering (ASE 2025) - Industry Showcase
22nd International Conference on Mining Software Repositories (MSR 2025) - Junior PC-track
22nd International Conference on Mining Software Repositories (MSR 2025) - Data and Tool Showcase Track
32nd IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2025) - Industrial Track
ChinaSoft 2024 - Foundation Models for Software Engineering Track
1st AI Foundation Models and Software Engineering (FORGE 2024) - Research Track

Journal Reviewer

ACM Transactions on Software Engineering and Methodology (TOSEM)
Journal of Software: Practice and Experience (JSPE)
IEEE Software
Automated Software Engineering Journal (ASEJ)
Empirical Software Engineering (EMSE)