May 21st, 2021. "Fairea: A Model Behaviour Mutation Approach to Benchmarking Bias Mitigation Methods" (by Max Hort, Jie M. Zhang, Federica Sarro, Mark Harman) is accepted by FSE 2021.
May 10th, 2021. Check Facebook's vision on Cyber–Cyber and Cyber–Physical Digital Twins!
Jan 8th 2021. "'Ignorance and Prejudice' in Software Fairness" (by Jie M. Zhang and Mark Harman) is accepted by ICSE 2021. [Short video]
Mutation 2020 is coming (24th Oct, 2020). More informatio: https://mutation-workshop.github.io/2020/#program Look forward to meeting you there!
Sep 2nd. Invited talk at The Hong Kong University of Science and Technology: Machine Learning Testing.
May 19th. "FrUITeR - A 𝐅𝐫amework for Evaluating 𝐔𝐈 𝐓𝐞st 𝐑euse " (by Yixue Zhao, Justin Chen, Adriana Sejfia, Marcelo Schmitt Laser, Jie M. Zhang, Federica Sarro, Mark Harman, Nenad Medvidović) is accepted to FSE2020.
May 19th. APSEC 2020 is calling for papers, welcome to submit your papers!
May 17th. STVR special issue: Mutation Analysis and Its Industrial Applications is calling for papers! Welcome to submit your papers!
Feb 13th, 2020. Invited talk at Facebook London: Perturbation Validation: A New Heuristic to Validate Machine Learning Models.
Dec 8th, 2019. "Automatic Testing and Improvement of Machine Translation" (by Zeyu Sun, Jie M. Zhang (co-first author), Mark Harman, Mike Papadakis, Lu Zhang) has been accepted by ICSE2020.
Nov 25th, 2019. "Machine Learning Testing: Survey, Landscapes and Horizons" (by Jie M. Zhang, Mark Harman, Lei Ma, Yang Liu) has been fully accepted by TSE (with one round of minor revision).
Oct 10th, 2019. Our paper "A Study of Programming Languages and Their Bug Resolution Characteristics" has been accepted by TSE (with one round of revision).
June 26th, 2019. Our survey Machine Learning Testing: Survey, Landscapes and Horizons is on arXiv. Any comments are welcome!
I am invited to give a talk at Queen Mary University on Machine Learning Testing, on June 26th, 2019 [slides].
Feb 12, 2019. One paper accepted by Mutation19: An Empirical Comparison of Mutant Selection Assessment Metrics, by Jie M. Zhang, Lingming Zhang, Dan Hao, Lu Zhang, Mark Harman
Dec 18, 2018. One paper accepted by ICST 2019: Do Pseudo Test Suites Lead to Inflated Correlation in Measuring Test Effectiveness? by Jie Zhang, Lingming Zhang, Dan Hao, Meng Wang, Lu Zhang.
One paper accepted by FSE 2018 industry track: Automated Refactoring of Nested-IF Formulae in Spreadsheets, by Jie Zhang, Shi Han, Dan Hao, Lu Zhang, Dongmei Zhang
I got the Outstanding PHD Graduate Award at Peking University
My research focus is to build more channels between SE and AI to make each community benefit more from the other. My past research has applied AI to SE, i.e., to use search-based techniques to automatically infer test oracles (ASE 2014), and to use machine learning techniques to automatically predicting the program behaviours (ISSTA 2016, TSE 2018). Currently, I am trying to combine my expertise in SE (e.g., code mutation and metamorphic testing) and AI (e.g., search algorithms) to improve automatic program debugging, as well as to apply SE methodology to AI to detect overfitting.
I mainly work with Prof. Mark Harman.
Major Research Experience
PHD student | Sep, 2015 – June, 2018 | GOSTA, Peking University, China | Supervisor : Lu Zhang and Dan Hao
Honors and Awards
2018 Outstanding PHD Graduate Award, Peking University
2017 Top-ten Research Excellence Award, EECS, Peking University
2016 Lee Wai Wing Scholarship at Peking University
2015 National Scholarship
2015 Award for Scientific Research
2014 Learning Scholarship at Peking University
2014 Award for Scientific Research
2014 Innovation Award at Peking University
2013 Learning Excellence Award at Peking University