7 papers
SEDCoT: Enhancing LLM-Based COBOL Code Translation via Symbolic Execution and Delta Debugging
Phillip Entin, Wenchao Gu, Alexander Knapp +1
COBOL remains critical across banking, insurance, and government infrastructure. However, maintenance is increasingly challenging due to outdated technologies, sparse documentation…
Evaluating LLMs on Real-World Software Performance Optimization
Ezgi Sarıkayak, Wenchao Gu, Hesham Ghonim +1
Software performance optimization is a notoriously complex and manual task. Despite the growing use of Large Language Models (LLMs) for code refinement, we still lack benchmarks th…
An Empirical Study of Agent Developer Practices in AI Agent Frameworks
Yanlin Wang, Xinyi Xu, Jiachi Chen +3
The rise of large language models (LLMs) has sparked a surge of interest in agents, leading to the rapid growth of agent frameworks. Agent frameworks are software toolkits and libr…
Weakly Supervised Vulnerability Localization via Multiple Instance Learning
Wenchao Gu, Yupan Chen, Yanlin Wang +3
Software vulnerability detection has emerged as a significant concern in the field of software security recently, capturing the attention of numerous researchers and developers. Mo…
SPENCER: Self-Adaptive Model Distillation for Efficient Code Retrieval
Wenchao Gu, Zongyi Lyu, Yanlin Wang +3
Code retrieval aims to provide users with desired code snippets based on users' natural language queries. With the development of deep learning technologies, adopting pre-trained m…
What to Retrieve for Effective Retrieval-Augmented Code Generation? An Empirical Study and Beyond
Wenchao Gu, Juntao Chen, Yanlin Wang +6
Repository-level code generation remains challenging due to complex code dependencies and the limitations of large language models (LLMs) in processing long contexts. While retriev…