4 citations · 14 across the 7 of their papers we have counts for
7 papers
Bridging Expert Knowledge with Deep Learning Techniques for Just-In-Time Defect Prediction
Xin Zhou, DongGyun Han, David Lo
Just-In-Time (JIT) defect prediction aims to automatically predict whether a commit is defective or not, and has been widely studied in recent years. In general, most studies can b…
Multi-LLM Collaboration + Data-Centric Innovation = 2x Better Vulnerability Repair
Xin Zhou, Kisub Kim, Bowen Xu +2
The advances of deep learning (DL) have paved the way for automatic software vulnerability repair approaches, which effectively learn the mapping from the vulnerable code to the fi…
CCBERT: Self-Supervised Code Change Representation Learning
Xin Zhou, Bowen Xu, DongGyun Han +3
Numerous code changes are made by developers in their daily work, and a superior representation of code changes is desired for effective code change analysis. Recently, Hoang et al…
The Devil is in the Tails: How Long-Tailed Code Distributions Impact Large Language Models
Xin Zhou, Kisub Kim, Bowen Xu +3
Learning-based techniques, especially advanced Large Language Models (LLMs) for code, have gained considerable popularity in various software engineering (SE) tasks. However, most…
Generation-based Code Review Automation: How Far Are We?
Xin Zhou, Kisub Kim, Bowen Xu +3
Code review is an effective software quality assurance activity; however, it is labor-intensive and time-consuming. Thus, a number of generation-based automatic code review (ACR) a…
Prioritizing Speech Test Cases
Zhou Yang, Jieke Shi, Muhammad Hilmi Asyrofi +4
With the wide adoption of automated speech recognition (ASR) systems, it is increasingly important to test and improve ASR systems. However, collecting and executing speech test ca…