Selected Conference Publications

* Papers with  bold titles are published in top-tier conferences 

Xin-Cheng Wen, Yupan Chen, Cuiyun Gao, Hongyu Zhang, Jie  Zhang, Qing Liao, “Vulnerability Detection with Graph Simplification and Enhanced  Graph Representation Learning”, ICSE 2023, to appear. 

Kaibo Liu, Yudong Han, Jie Zhang, Zhenpeng Chen, Federica Sarro, Mark Harman, Gang Huang, Yun Ma, “Who Judges the Judge: An Empirical Study on Online Judge Tests”, ISSTA 2023, to appear.

Qingchao Shen, Junjie Chen, Jie Zhang, Haoyu Wang, Shuang Liu, Menghan Tian, “Natural Test Generation for Precise Testing of Question Answering Software”, ASE 2022 (acceptane rate: 21.8%), pp.1-12. October 2022.

Zhenpeng Chen, Jie Zhang, Federica Sarro, Mark Harman, “MAAT: A Novel Ensemble Approach to Fixing Fairness and Performance Bugs for Machine Learning Software”, FSE 2022 (acceptance rate 22%), pp. 1122-1134, November 2022.

Baptiste Roziere, Jie Zhang, Francois Charton, Mark Harman, Gabriel Synnaeve, Guillaume Lample, “Leveraging Automated Unit Tests for Unsupervised Code Translation”, ICLR 2022 Spotlight (acceptance rate 5%), April 2022.

Zeyu Sun, Jie Zhang, Yingfei Xiong, Mark Harman, Mike Papadakis, Lu Zhang, “Improving Machine Translation Systems via Isotopic Replacement”, ICSE 2022 (acceptance rate 26%), pp.1181-1192, May 2022

Wei Ma, Mengjie Zhao, Ezekiel Soremekun, Qiang Hu, Jie Zhang, Mike Papadakis, Maxime Cordy, Xiaofei Xie, Yves Le Traon, “Using Lexical and Semantic Program Features to form Generic Code Representation”, MSR 2022 (acceptance rate 34%), pp.524-536, May 2022.

Max Hort, Jie Zhang, Federica Sarro, Mark Harman, “Fairea: A Model Behaviour Mutation Approach to Benchmarking Bias Mitigation Methods”, FSE 2021 (acceptance rate 24.5%), pp.994-1006, August,2021.

Jie Zhang, Mark Harman, “ ‘Ignorance and Prejudice’ in Software Fairness”, ICSE 2021 (acceptance rate 22.9%), pp.1436-1447, May 2021. 

Jie Zhang, Zeyu Sun, Mark Harman, Mike Papadakis, Lu Zhang, “Automatic Testing and Improvement of Machine Translation”,  ICSE 2020 (acceptance rate 21%), pp. 974-985, July 2020.

Yixue Zhao, Justin Chen, Adriana Sejfia, Marcelo Schmitt Laser, Jie Zhang, Federica Sarro, Mark Harman, Nenad Medvidović, “FrUITeR - A Framework for Evaluating UI Test Reuse”,  FSE 2020 (acceptance rate 28%), pp. 1190-1201, November, 2020.

Jie Zhang, Shi Han, Dan Hao, Lu Zhang, Dongmei Zhang, “Automated Refactoring of Nested-IF Formulae in Spreadsheets”, ESEC/FSE 2018 industry track, pp. 833-838, November 2018.

Jie Zhang, Lingming Zhang, Dan Hao, Meng Wang, Lu Zhang, “Do pseudo test suites lead to inflated correlation in measuring test effectiveness?”, ICST 2019 (acceptance rate 29%), pp. 252-263, 2019.

Jie Zhang, Yiling Lou, Lingming Zhang, Dan Hao, Lu Zhang, Hong Mei, “Isomorphic Regression Testing: Executing Uncovered Branches without Test Augmentation”, FSE 2016 (acceptance rate 27%), pp. 883-894, November 2016.

Jie Zhang, Ziyi Wang, Lingming Zhang, Dan Hao, Lei Zang, Shiyang Cheng, Lu Zhang, “Predictive Mutation Testing”, ISSTA 2016 (acceptance rate 26%), pp. 342-353, June 2016.

Jie Zhang, Junjie Chen, Dan Hao, Yingfei Xiong, Bing Xie, Lu Zhang, and Hong Mei, “Search-based Inference of Polynomial Metamorphic Relations”, ASE 2014 (acceptance rate 24%), pp. 701-712, September 2014.

Jie Zhang, Muyao Zhu, Dan Hao, and Lu Zhang, “An Empirical Study on the Scalability of Selective Mutation Testing”, ISSRE 2014, pp. 277-287, October 2014.

Jie Zhang, Dan Hao, Lingming Zhang, Lu Zhang, “To Detect Abnormal Program Behaviours via Mutation Deduction”, Mutation 2018, pp. 11-17, April 2018.

Jie Zhang, Lingming Zhang, Dan Hao, Lu Zhang, Mark Harman, “An Empirical Comparison of Mutant Selection Assessment Metrics'”, Mutation 2019.

Selected Journal Publications

* Papers with bold titles are published in CORE A*  journals 

Zhenpeng Chen, Jie  Zhang, Federica Sarro, Mark Harman, “A Comprehensive Empirical Study of Bias Mitigation Methods for Machine Learning Classifiers”, ACM Transactions on Software Engineering and Methodology 2023.

Jie Zhang, Mark Harman, Benjamin Guedj, Earl Barr, John Shawe-Taylor, “Model Validation Using Mutated Training Labels: An Exploratory Study”, Neurocomputing 2023.

Jie Zhang, Mark Harman, Lei Ma, Yang Liu, “Machine Learning Testing: Survey, Landscapes and Horizons”, IEEE Transactions on Software Engineering  2020. 

Jie Zhang, Feng Li, Dan Hao, Meng Wang, Hao Tang, Lu Zhang, Mark Harman, “A Study of Bug Resolution Characteristics in Popular Programming Languages”, IEEE Transactions on Software Engineering 2019. 

Jie Zhang,  Lingming Zhang, Mark Harman, Dan Hao, Yue Jia, Lu Zhang, “Predictive Mutation Testing”, IEEE Transactions on Software Engineering 2018.

Mike Papadakis, Marinos Kintis, Jie Zhang, Yue Jia, Yves Le Traon and Mark Harman, “Mutation Testing Advances: An Analysis and Survey”, Advances in Computers 2018.

Jie Zhang, Xiaoyin Wang, Dan Hao, Bing Xie, Lu Zhang, Hong Mei, “A Survey on Bug-report Analysis'”, Science China Information Sciences, 58(2), pp 1-24, 2014.