12 citations · 32 across the 21 of their papers we have counts for
21 papers
Designing LLM-based Multi-Agent Systems for Software Engineering Tasks: Quality Attributes, Design Patterns and Rationale
Yangxiao Cai, Ruiyin Li, Peng Liang +4
As the complexity of Software Engineering (SE) tasks continues to escalate, Multi-Agent Systems (MASs) have emerged as a focal point of research and practice due to their autonomy…
FasterPy: An LLM-based Code Execution Efficiency Optimization Framework
Yue Wu, Minghao Han, Ruiyin Li +5
Code often suffers from performance bugs. These bugs necessitate the research and practice of code optimization. Traditional rule-based methods rely on manually designing and maint…
Unveiling the Role of ChatGPT in Software Development: Insights from Developer-ChatGPT Interactions on GitHub
Ruiyin Li, Peng Liang, Yifei Wang +3
The advent of Large Language Models (LLMs) has introduced a new paradigm in Software Engineering (SE), with generative AI tools like ChatGPT gaining widespread adoption among devel…
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…
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…
Demystifying Issues, Causes and Solutions in LLM Open-Source Projects
Yangxiao Cai, Peng Liang, Yifei Wang +2
With the advancements of Large Language Models (LLMs), an increasing number of open-source software projects are using LLMs as their core functional component. Although research an…
Bug Priority Change: An Empirical Study on Apache Projects
Zengyang Li, Guangzong Cai, Qinyi Yu +3
In issue tracking systems, each bug is assigned a priority level (e.g., Blocker, Critical, Major, Minor, or Trivial in JIRA from highest to lowest), which indicates the urgency lev…
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 Multi-Programming-Language Commits and Their Impacts on Software Quality: An Empirical Study on Apache Projects
Zengyang Li, Xiaoxiao Qi, Qinyi Yu +3
Context: Modern software systems (e.g., Apache Spark) are usually written in multiple programming languages (PLs). There is little understanding on the phenomenon of multi-programm…
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…
Security Weaknesses of Copilot-Generated Code in GitHub Projects: An Empirical Study
Yujia Fu, Peng Liang, Amjed Tahir +4
Modern code generation tools utilizing AI models like Large Language Models (LLMs) have gained increased popularity due to their ability to produce functional code. However, their…
Understanding Resolution of Multi-Language Bugs: An Empirical Study on Apache Projects
Zengyang Li, Wenshuo Wang, Sicheng Wang +2
Background: In modern software systems, more and more systems are written in multiple programming languages (PLs). There is no comprehensive investigation on the phenomenon of mult…
Understanding Bugs in Multi-Language Deep Learning Frameworks
Zengyang Li, Sicheng Wang, Wenshuo Wang +3
Deep learning frameworks (DLFs) have been playing an increasingly important role in this intelligence age since they act as a basic infrastructure for an increasingly wide range of…
Technical Debt Management in OSS Projects: An Empirical Study on GitHub
Zengyang Li, Yilin Peng, Peng Liang +4
Technical debt (TD) refers to delayed tasks and immature artifacts that may bring short-term benefits but incur extra costs of change during maintenance and evolution in the long t…
Mining Architectural Information: A Systematic Mapping Study
Musengamana Jean de Dieu, Peng Liang, Mojtaba Shahin +2
Mining Software Repositories (MSR) has become an essential activity in software development. Mining architectural information to support architecting activities, such as architectu…
Potential Technical Debt and Its Resolution in Code Reviews: An Exploratory Study of the OpenStack and Qt Communities
Liming Fu, Peng Liang, Zeeshan Rasheed +3
Technical Debt (TD) refers to the situation where developers make trade-offs to achieve short-term goals at the expense of long-term code quality, which can have a negative impact…
Decisions in Continuous Integration and Delivery: An Exploratory Study
Yajing Luo, Peng Liang, Mojtaba Shahin +2
In recent years, Continuous Integration (CI) and Continuous Delivery (CD) has been heatedly discussed and widely used in part or all of the software development life cycle as the p…
Self-Claimed Assumptions in Deep Learning Frameworks: An Exploratory Study
Chen Yang, Peng Liang, Liming Fu +1
Deep learning (DL) frameworks have been extensively designed, implemented, and used in software projects across many domains. However, due to the lack of knowledge or information,…
Multi-Programming-Language Commits in OSS: An Empirical Study on Apache Projects
Zengyang Li, Xiaoxiao Qi, Qinyi Yu +3
Modern software systems, such as Spark, are usually written in multiple programming languages (PLs). Besides benefiting from code reuse, such systems can also take advantages of sp…
Automatic Detection of Public Development Projects in Large Open Source Ecosystems: An Exploratory Study on GitHub
Can Cheng, Bing Li, Zengyang Li +1
Hosting over 10 million of software projects, GitHub is one of the most important data sources to study behavior of developers and software projects. However, with the increase of…