Haoye TIAN (田 昊野)

Postdoctoral Fellow at The University of Melbourne

Contact:

Address: 700 Swanston St, Carlton VIC 3053, Australia
Email: haoye.tian unimelb.edu.au
Twitter: Haoye TIAN


I am a postdoctoral fellow in the School of Computing and Information Systems at University of Melbourne , working with Prof. Bach Le. Prior to that, I was a postdoctoral researcher and pursued my Ph.D. degree in the SnT, University of Luxembourg under the supervision of Prof. Tegawendé F. Bissyandé and Prof. Jacques Klein. During my post in Luxembourg, I visited and collaborated with Prof. Claire Le Goues as a visiting scholar at Carnegie Mellon University, and Prof. Shing-Chi Cheung as a visiting Ph.D. student at Hong Kong University of Science and Technology. I obtained my master degree from Chongqing University, under the supervision of Prof. Haini Cai and Prof. Junhao Wen. I worked as a machine learning researcher at Tencent and Didi.

Research interests:

Google Scholar / DBLP / ORCID

News

Selected Publications

Pre-print

Haoye Tian, Weiqi Lu, Tsz On Li, Xunzhu Tang, Shing-Chi Cheung, Jacques Klein, Tegawendé F. Bissyandé. Is ChatGPT the Ultimate Programming Assistant-How far is it?

EMNLP'24

Daniel Tang, Kisub Kim, Yewei Song, Cedric Lothritz, Bei Li, Saad Ezzini, Haoye Tian, Jacques Klein, and Tegawendé F. Bissyandé. CodeAgent: Autonomous Communicative Agents for Code Review. The 2024 Conference on Empirical Methods in Natural Language Processing.

ISSTA'24

Boyang Yang#, Haoye Tian#, Weiguo Pian, Haoran Yu, Haitao Wang, Jacques Klein, Tegawendé F Bissyandé, Shunfu Jin. CREF: An LLM-based Conversational Software Repair Framework for Programming Tutors. The 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2024.

CSCW'24

Yuwei Chuai, Haoye Tian, Nicolas Pröllochs, and Gabriele Lenzini. Did the Roll-Out of Community Notes Reduce Engagement With Misinformation on X/Twitter? The 27th ACM Conference on Computer-Supported Cooperative Work and Social Computing, 2024.

ASE'23

Tsz-On Li, Wenxi Zong, Yibo Wang, Haoye Tian, Ying Wang, Shing-Chi Cheung. Nuances are the Key: Unlocking ChatGPT to Find Failure-Inducing Tests with Differential Prompting The 38th IEEE/ACM International Conference on Automated Software Engineering, 2023.

AAAI'23

Weiguo Pian, Hanyu Peng, Xunzhu Tang, Tiezhu Sun, Haoye Tian*, Andrew Habib, Jacques Klein, Tegawendé F Bissyandé. MetaTPTrans: A Meta Learning Approach for Multilingual Code Representation Learning The 37th AAAI Conference on Artificial Intelligence, 2023. [Acceptance rate: 19.6% (1,721/8,777)]

TOSEM'23

Haoye Tian, Kui Liu*, Yinghua Li, Abdoul Kader Kaboré, Anil Koyuncu, Andrew Habib, Li Li, Junhao Wen, Jacques Klein, Tegawendé F Bissyandé. The Best of Both Worlds: Combining Learned Embeddings with Engineered Features for Accurate Prediction of Correct Patches ACM Transactions on Software Engineering and Methodology, 2023.

ASE'22

Haoye Tian, Xunzhu Tang, Andrew Habib, Shangwen Wang, Kui Liu*, Xin Xia, Jacques Klein, Tegawendé F. Bissyandé. Is this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness The 37th IEEE/ACM International Conference on Automated Software Engineering, 2022. [Acceptance rate: 14.8% (78/527)]

TOSEM'22
ICSE'23 JF

Haoye Tian, Yinghua Li, Weiguo Pian, Abdoul Kader Kabore, Kui Liu*, Andrew Habib, Jacques Klein, and Tegawendé F. Bissyandé. Predicting Patch Correctness Based on the Similarity of Failing Test Cases ACM Transactions on Software Engineering and Methodology, 2022.

ASE'20

Haoye Tian, Kui Liu*, Abdoul Kader Kaboré, Anil Koyuncu, Li Li, Jacques Klein, Tegawendé F. Bissyandé. Evaluating Representation Learning of Code Changes for Predicting Patch Correctness in Program Repair The 35th IEEE/ACM International Conference on Automated Software Engineering, 2020. [Acceptance rate: 22.28% (88/395)]

IJCNN'19

Haoye Tian, Haini Cai, Junhao Wen, Shun Li, Yingqiao Li. A Music Recommendation System Based on logistic regression and eXtreme Gradient Boosting 2019 International Joint Conference on Neural Networks, Budapest, Hungary, July, 14-19 2019. IEEE.

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