1 citations · 1 across the 2 of their papers we have counts for
5 papers
Reducing False Positives in Static Bug Detection with LLMs: An Empirical Study in Industry
Xueying Du, Jiayi Feng, Yi Zou +6
Static analysis tools (SATs) are widely adopted in both academia and industry for improving software quality, yet their practical use is often hindered by high false positive rates…
Minimizing False Positives in Static Bug Detection via LLM-Enhanced Path Feasibility Analysis
Xueying Du, Kai Yu, Chong Wang +6
Static bug analyzers play a crucial role in ensuring software quality. However, existing analyzers for bug detection in large codebases often suffer from high false positive rates.…
PromCopilot: Simplifying Prometheus Metric Querying in Cloud Native Online Service Systems via Large Language Models
Chenxi Zhang, Bicheng Zhang, Dingyu Yang +6
With the increasing complexity of modern online service systems, understanding the state and behavior of the systems is essential for ensuring their reliability and stability. Ther…
TransAgent: Enhancing LLM-Based Code Translation via Fine-Grained Execution Alignment
Zhiqiang Yuan, Weitong Chen, Hanlin Wang +3
Code translation transforms code between programming languages while preserving functionality, which is critical in software development and maintenance. While traditional learning…
Large Language Model-Based Agents for Software Engineering: A Survey
Junwei Liu, Kaixin Wang, Yixuan Chen +4
The recent advance in Large Language Models (LLMs) has shaped a new paradigm of AI agents, i.e., LLM-based agents. Compared to standalone LLMs, LLM-based agents substantially exten…