4 citations · 9 across the 7 of their papers we have counts for
9 papers
Benchmarking and Enhancing Design-Aware Code Review in the Linux Kernel
Zhenhao Zhou, Kai Yu, Ying Wang +5
Code review often requires reasoning beyond local correctness. In mature software systems, reviewers must recognize design trade-offs introduced by a proposed change, compare alter…
Does Pass Rate Tell the Whole Story? Evaluating Design Constraint Compliance in LLM-based Issue Resolution
Kai Yu, Zhenhao Zhou, Junhao Zeng +8
Repository-level issue resolution benchmarks have become a standard testbed for evaluating LLM-based agents, yet success is still predominantly measured by test pass rates. In prac…
Towards Iterative End-to-End Software Development: A Feature-Driven Multi-Agent Framework
Junwei Liu, Chen Xu, Chong Wang +5
Recent advances in large language model agents offer the promise of automating end-to-end software development from natural language requirements. However, existing approaches larg…
Extracting Conceptual Knowledge to Locate Software Issues
Ying Wang, Wenjun Mao, Chong Wang +5
Issue localization, which identifies faulty code elements such as files or functions, is critical for effective bug fixing. While recent LLM-based and LLM-agent-based approaches im…
Project-Level C-to-Rust Translation via Pointer Knowledge Graphs
Zhiqiang Yuan, Wenjun Mao, Zhuo Chen +4
Translating C code into safe Rust is an effective way to ensure memory safety. Compared to rule-based approaches, which often produce largely unsafe Rust code, LLM-based methods ge…
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.…
Taming System Complexity: Demystifying Software Engineering Agents in Diagnosing Linux Kernel Faults
Zhenhao Zhou, Zhuochen Huang, Yike He +5
The Linux kernel is a critical system, serving as the foundation for numerous systems. Bugs in the Linux kernel can cause serious consequences, affecting billions of users. Fault l…
Benchmarking LLMs and LLM-based Agents in Practical Vulnerability Detection for Code Repositories
Alperen Yildiz, Sin G. Teo, Yiling Lou +3
Large Language Models (LLMs) have shown promise in software vulnerability detection, particularly on function-level benchmarks like Devign and BigVul. However, real-world detection…
Boosting Static Resource Leak Detection via LLM-based Resource-Oriented Intention Inference
Chong Wang, Jianan Liu, Xin Peng +2
Resource leaks, caused by resources not being released after acquisition, often lead to performance issues and system crashes. Existing static detection techniques rely on mechanic…