89 citations · 101 across the 25 of their papers we have counts for
8 papers · 1 filter
The Current Challenges of Software Engineering in the Era of Large Language Models
Cuiyun Gao, Xing Hu, Shan Gao +2
With the advent of large language models (LLMs) in the artificial intelligence (AI) area, the field of software engineering (SE) has also witnessed a paradigm shift. These models,…
Deep Learning-based Software Engineering: Progress, Challenges, and Opportunities
Xiangping Chen, Xing Hu, Yuan Huang +23
Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language p…
Automated Unit Test Refactoring
Yi Gao, Xing Hu, Xiaohu Yang +1
Test smells arise from poor design practices and insufficient domain knowledge, which can lower the quality of test code and make it harder to maintain and update. Manually refacto…
Vulnerability-Triggering Test Case Generation from Third-Party Libraries
Yi Gao, Xing Hu, Zirui Chen +1
Open-source third-party libraries are widely used in software development. These libraries offer substantial advantages in terms of time and resource savings. However, a significan…
GUIMigrator: Semantics-Preserving Transpilation from Android XML to Compose and SwiftUI
Yi Gao, Xing Hu, Xin Xia +1
Constructing user interfaces (UIs) is one of the most resource-intensive tasks in mobile development, often consuming more than half of overall effort. Although declarative framewo…
Where Is Self-admitted Code Generated by Large Language Models on GitHub?
Xiao Yu, Lei Liu, Xing Hu +2
The increasing use of Large Language Models (LLMs) in software development has garnered significant attention from researchers evaluating the capabilities and limitations of LLMs f…
CATCODER: Repository-Level Code Generation with Relevant Code and Type Context
Zhiyuan Pan, Xing Hu, Xin Xia +1
Large language models (LLMs) have demonstrated remarkable capabilities in code generation tasks. However, repository-level code generation presents unique challenges, particularly…
Refactoring Deep Learning Code: A Study of Practices and Unsatisfied Tool Needs
Siqi Wang, Xing Hu, Bei Wang +3
With the rapid development of deep learning, the implementation of intricate algorithms and substantial data processing have become standard elements of deep learning projects. As…