27 citations · 42 across the 24 of their papers we have counts for
8 papers · 1 filter
Discovery of Timeline and Crowd Reaction of Software Vulnerability Disclosures
Yi Wen Heng, Zeyang Ma, Haoxiang Zhang +3
Reusing third-party libraries increases productivity and saves time and costs for developers. However, the downside is the presence of vulnerabilities in those libraries, which can…
Studying and Benchmarking Large Language Models For Log Level Suggestion
Yi Wen Heng, Zeyang Ma, Zhenhao Li +3
Large Language Models (LLMs) have become a focal point of research across various domains, including software engineering, where their capabilities are increasingly leveraged. Rece…
Understanding Practitioners' Expectations on Clear Code Review Comments
Junkai Chen, Zhenhao Li, Qiheng Mao +3
The code review comment (CRC) is pivotal in the process of modern code review. It provides reviewers with the opportunity to identify potential bugs, offer constructive feedback, a…
ThinkRepair: Self-Directed Automated Program Repair
Xin Yin, Chao Ni, Shaohua Wang +3
Though many approaches have been proposed for Automated Program Repair (APR) and indeed achieved remarkable performance, they still have limitations in fixing bugs that require ana…
NLPerturbator: Studying the Robustness of Code LLMs to Natural Language Variations
Junkai Chen, Zhenhao Li, Xing Hu +1
Large language models (LLMs) achieve promising results in code generation based on a given natural language description. They have been integrated into open-source projects and com…
Towards Explainable Vulnerability Detection with Large Language Models
Qiheng Mao, Zhenhao Li, Xing Hu +3
Software vulnerabilities pose significant risks to the security and integrity of software systems. Although prior studies have explored vulnerability detection using deep learning…
A Roadmap on Modern Code Review: Challenges and Opportunities
Zezhou Yang, Cuiyun Gao, Zhaoqiang Guo +4
Over the past decade, modern code review (MCR) has been established as a cornerstone of software quality assurance and a vital channel for knowledge transfer within development tea…
Reasoning Runtime Behavior of a Program with LLM: How Far Are We?
Junkai Chen, Zhiyuan Pan, Xing Hu +3
Large language models for code (i.e., code LLMs) have shown strong code understanding and generation capabilities. To evaluate the capabilities of code LLMs in various aspects, man…