34 citations · 165 across the 50 of their papers we have counts for
41 papers · 1 filter
Semantic-Enhanced Automatic Refinement of Architecture Recovery Results Using LLMs
Yiran Zhang, Chengwei Liu, Yuqiang Sun +5
Understanding the architecture is crucial for effectively maintaining and managing large software systems. However, discrepancies often exist between the designed and implemented a…
Understanding before Naming! Enhancing LLM-based Method Name Prediction with Code Summarization
Wei Liu, Weisong Sun, Tingting Xu +4
Method names are critical to software quality, affecting code comprehensibility, maintainability, and developer collaboration. However, manually designing meaningful method names i…
DeepDiscovery: A Location-Inference Framework for Task-Level Repository Understanding
Jiawei He, Weisong Sun, Mengyu Shi +4
Large language models have shown strong performance on software engineering (SE) tasks, yet understanding large industrial repositories remains challenging. Existing methods often…
Bridging Requirements and Architecture: Multi-Agent Orchestration with External Knowledge and Hierarchical Memory
Ruiyin Li, Yiran Zhang, Xiyu Zhou +6
Software architecture design is a critical yet inherently complex and knowledge-intensive phase that requires balancing competing quality attributes and adapting to evolving requir…
Probing Privacy Leaks in LLM-based Code Generation via Test Generation
Yifei Ge, Zhenpeng Chen, Weisong Sun +7
The widespread availability of large-scale code datasets has fueled the rapid development of large language models (LLMs) for code-related tasks. These datasets may include sensiti…
How Effective Are NPM Malicious Package Detectors? A Large-Scale Empirical Study
Wenbo Guo, Zhongwen Chen, Zhengzi Xu +7
The NPM ecosystem faces escalating threats from malicious packages that exploit its open publication model. While numerous detection tools have been proposed, they are evaluated on…
TraceCoder: A Trace-Driven Multi-Agent Framework for Automated Debugging of LLM-Generated Code
Jiangping Huang, Wenguang Ye, Weisong Sun +3
Large Language Models (LLMs) often generate code with subtle but critical bugs, especially for complex tasks. Existing automated repair methods typically rely on superficial pass/f…
REprompt: Prompt Generation for Intelligent Software Development Guided by Requirements Engineering
Junjie Shi, Weisong Sun, Zhenpeng Chen +4
The rapid development of large language models is transforming software development. Beyond serving as code auto-completion tools in integrated development environments, large lang…
Hallucination Detection for LLM-based Text-to-SQL Generation via Two-Stage Metamorphic Testing
Bo Yang, Yinfen Xia, Weisong Sun +1
In Text-to-SQL generation, large language models (LLMs) have shown strong generalization and adaptability. However, LLMs sometimes generate hallucinations, i.e.,unrealistic or illo…
Knowledge-Guided Multi-Agent Framework for Application-Level Software Code Generation
Qian Xiong, Bo Yang, Weisong Sun +4
Automated code generation driven by Large Lan- guage Models (LLMs) has enhanced development efficiency, yet generating complex application-level software code remains challenging.…
UserTrace: User-Level Requirements Generation and Traceability Recovery from Software Project Repositories
Dongming Jin, Zhi Jin, Yiran Zhang +5
Software maintainability critically depends on high-quality requirements descriptions and explicit traceability between requirements and code. Although automated code summarization…
Requirements Development and Formalization for Reliable Code Generation: A Multi-Agent Vision
Xu Lu, Weisong Sun, Yiran Zhang +4
Automated code generation has long been considered the holy grail of software engineering. The emergence of Large Language Models (LLMs) has catalyzed a revolutionary breakthrough…
MAAD: Automate Software Architecture Design through Knowledge-Driven Multi-Agent Collaboration
Ruiyin Li, Yiran Zhang, Xiyu Zhou +5
Software architecture design is a critical, yet inherently complex and knowledge-intensive phase of software development. It requires deep domain expertise, development experience,…
iReDev: A Knowledge-Driven Multi-Agent Framework for Intelligent Requirements Development
Dongming Jin, Weisong Sun, Jiangping Huang +4
Requirements development is a critical phase as it is responsible for providing a clear understanding of what stakeholders need. It involves collaboration among stakeholders to ext…
Knowledge-Guided Multi-Agent Framework for Automated Requirements Development: A Vision
Jiangping Huang, Dongming Jin, Weisong Sun +2
This paper envisions a knowledge-guided multi-agent framework named KGMAF for automated requirements development. KGMAF aims to address gaps in current automation systems for SE, w…
Software Development Life Cycle Perspective: A Survey of Benchmarks for Code Large Language Models and Agents
Kaixin Wang, Tianlin Li, Xiaoyu Zhang +7
Code large language models (CodeLLMs) and agents are increasingly being integrated into complex software engineering tasks spanning the entire Software Development Life Cycle (SDLC…
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…
Knowledge-Based Multi-Agent Framework for Automated Software Architecture Design
Yiran Zhang, Ruiyin Li, Peng Liang +2
Architecture design is a critical step in software development. However, creating a high-quality architecture is often costly due to the significant need for human expertise and ma…
Commenting Higher-level Code Unit: Full Code, Reduced Code, or Hierarchical Code Summarization
Weisong Sun, Yiran Zhang, Jie Zhu +8
Commenting code is a crucial activity in software development, as it aids in facilitating future maintenance and updates. To enhance the efficiency of writing comments and reduce d…
Promptware Engineering: Software Engineering for Prompt-Enabled Systems
Zhenpeng Chen, Chong Wang, Weisong Sun +3
Large Language Models (LLMs) are increasingly integrated into software applications, giving rise to a broad class of prompt-enabled systems, in which prompts serve as the primary '…
TIGER: A Generating-Then-Ranking Framework for Practical Python Type Inference
Chong Wang, Jian Zhang, Yiling Lou +4
Python's dynamic typing system offers flexibility and expressiveness but can lead to type-related errors, prompting the need for automated type inference to enhance type hinting. W…
Source Code Summarization in the Era of Large Language Models
Weisong Sun, Yun Miao, Yuekang Li +6
To support software developers in understanding and maintaining programs, various automatic (source) code summarization techniques have been proposed to generate a concise natural…
ESALE: Enhancing Code-Summary Alignment Learning for Source Code Summarization
Chunrong Fang, Weisong Sun, Yuchen Chen +7
(Source) code summarization aims to automatically generate succinct natural language summaries for given code snippets. Such summaries play a significant role in promoting develope…
Towards Effective Detection of Ponzi schemes on Ethereum with Contract Runtime Behavior Graph
Ruichao Liang, Jing Chen, Cong Wu +6
Ponzi schemes, a form of scam, have been discovered in Ethereum smart contracts in recent years, causing massive financial losses. Existing detection methods primarily focus on rul…