67 citations · 85 across the 13 of their papers we have counts for
13 papers
Using LLMs in Generating Design Rationale for Software Architecture Decisions
Xiyu Zhou, Ruiyin Li, Peng Liang +4
Design Rationale (DR) for software architecture decisions refers to the reasoning underlying architectural choices, which provides valuable insights into the different phases of th…
LessLeak-Bench: A First Investigation of Data Leakage in LLMs Across 83 Software Engineering Benchmarks
Xin Zhou, Martin Weyssow, Ratnadira Widyasari +7
Large Language Models (LLMs) are widely utilized in software engineering (SE) tasks, such as code generation and automated program repair. However, their reliance on extensive and…
A Comprehensive Evaluation of Parameter-Efficient Fine-Tuning on Code Smell Detection
Beiqi Zhang, Peng Liang, Xin Zhou +5
Automated code smell detection faces persistent challenges due to the subjectivity of heuristic rules and the limited performance of traditional ML/DL models. While Large Language…
Copilot-in-the-Loop: Fixing Code Smells in Copilot-Generated Python Code using Copilot
Beiqi Zhang, Peng Liang, Qiong Feng +2
As one of the most popular dynamic languages, Python experiences a decrease in readability and maintainability when code smells are present. Recent advancements in Large Language M…
Architecture Decisions in Quantum Software Systems: An Empirical Study on Stack Exchange and GitHub
Mst Shamima Aktar, Peng Liang, Muhammad Waseem +4
Quantum computing provides a new dimension in computation, utilizing the principles of quantum mechanics to potentially solve complex problems that are currently intractable for cl…
Exploring the Problems, their Causes and Solutions of AI Pair Programming: A Study on GitHub and Stack Overflow
Xiyu Zhou, Peng Liang, Beiqi Zhang +4
With the recent advancement of Artificial Intelligence (AI) and Large Language Models (LLMs), AI-based code generation tools become a practical solution for software development. G…
Demystifying Practices, Challenges and Expected Features of Using GitHub Copilot
Beiqi Zhang, Peng Liang, Xiyu Zhou +2
With the advances in machine learning, there is a growing interest in AI-enabled tools for autocompleting source code. GitHub Copilot has been trained on billions of lines of open…
Demystifying Code Snippets in Code Reviews: A Study of the OpenStack and Qt Communities and A Practitioner Survey
Beiqi Zhang, Liming Fu, Peng Liang +2
Code review is widely known as one of the best practices for software quality assurance in software development. In a typical code review process, reviewers check the code committe…
Practices and Challenges of Using GitHub Copilot: An Empirical Study
Beiqi Zhang, Peng Liang, Xiyu Zhou +2
With the advances in machine learning, there is a growing interest in AI-enabled tools for autocompleting source code. GitHub Copilot, also referred to as the "AI Pair Programmer",…
Architecture Decisions in AI-based Systems Development: An Empirical Study
Beiqi Zhang, Tianyang Liu, Peng Liang +3
Artificial Intelligence (AI) technologies have been developed rapidly, and AI-based systems have been widely used in various application domains with opportunities and challenges.…
RoseMatcher: Identifying the Impact of User Reviews on App Updates
Tianyang Liu, Chong Wang, Kun Huang +4
: The release planning of mobile apps has become an area of active research, with most studies centering on app analysis through release notes in the Apple App St…
Understanding Code Snippets in Code Reviews: A Preliminary Study of the OpenStack Community
Liming Fu, Peng Liang, Beiqi Zhang
Code review is a mature practice for software quality assurance in software development with which reviewers check the code that has been committed by developers, and verify the qu…
3D Human Motion Prediction: A Survey
Kedi Lyu, Haipeng Chen, Zhenguang Liu +2
3D human motion prediction, predicting future poses from a given sequence, is an issue of great significance and challenge in computer vision and machine intelligence, which can he…