MOBILESoft 2022
Tue 17 - Wed 18 May 2022
co-located with ICSE 2022
Hongyu Zhang

Registered user since Sat 30 Dec 2017

Name:Hongyu Zhang
Bio:

Hongyu Zhang is currently an associate professor at The University of Newcastle, Australia. Previously, he was a Lead Researcher at Microsoft Research Asia and an Associate Professor at Tsinghua University, China. He received his PhD degree from National University of Singapore in 2003. His research is in the area of Software Engineering, in particular, software analytics, testing, maintenance, and reuse. The main theme of his research is to improve software quality and productivity by mining software data. He has published more than 160 research papers in international journals and conferences, including TSE, TOSEM, ICSE, FSE, POPL, AAAI, IJCAI, KDD, ASE, ISSTA, ICSME, ICDM, and USENIX. He received three ACM Distinguished Paper awards. He has also served as a program committee member for many software engineering conferences. More information about him can be found at: https://sites.google.com/site/hongyujohn/ .

Country:Australia
Affiliation:University of Newcastle
Research interests:Software analytics, testing, debugging, maintenance and reuse

Contributions

MSR 2022 LibDB: An Effective and Efficient Framework for Detecting Third-Party Libraries in Binaries
Committee Member in Program Committee within the Technical Papers-track
Session Chair of Session 1 (part of Technical Papers)
Committee Member in Shadow PC Advisors within the Shadow PC-track
ICPC 2022 HELoC: Hierarchical Contrastive Learning of Source Code Representation
ICSE 2022 Where is Your App Frustrating Users?
Log-based Anomaly Detection with Deep Learning: How Far Are We
Cross-Domain Deep Code Search with Few-Shot Learning
What Do They Capture? - A Structural Analysis of Pre-Trained Language Models for Source Code
NaturalCC: An Open-Source Toolkit for Code Intelligence
On the Evaluation of Neural Code Summarization
Refty: Refinement Types for Valid Deep Learning Models
Adaptive Performance Anomaly Detection for Online Service Systems via Pattern Sketching
Improving Fault Localization and Program Repair with Deep Semantic Features and Transferred Knowledge
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