10 citations · 25 across the 13 of their papers we have counts for
7 papers · 1 filter
Aligning Academia with Industry: An Empirical Study of Industrial Needs and Academic Capabilities in AI-Driven Software Engineering
Hang Yu, Yuzhou Lai, Li Zhang +6
The rapid advancement of large language models (LLMs) is fundamentally reshaping software engineering (SE), driving a paradigm shift in both academic research and industrial practi…
SecureReviewer: Enhancing Large Language Models for Secure Code Review through Secure-aware Fine-tuning
Fang Liu, Simiao Liu, Yinghao Zhu +2
Identifying and addressing security issues during the early phase of the development lifecycle is critical for mitigating the long-term negative impacts on software systems. Code r…
An Empirical Study on Failures in Automated Issue Solving
Simiao Liu, Fang Liu, Liehao Li +4
Automated issue solving seeks to autonomously identify and repair defective code snippets across an entire codebase. SWE-Bench has emerged as the most widely adopted benchmark for…
Vision to Specification: Automating the Transition from Conceptual Features to Functional Requirements
Xiaoli Lian, Jiajun Wu, Xiaoyun Gao +2
The translation of high-level abstract features into clear, and testable functional requirements (FRs) is a crucial step in software development, bridging the gap between user need…
Incorporating Verification Standards for Security Requirements Generation from Functional Specifications
Xiaoli Lian, Shuaisong Wang, Hanyu Zou +3
In the current software driven era, ensuring privacy and security is critical. Despite this, the specification of security requirements for software is still largely a manual and l…
Revolutionizing Newcomers' Onboarding Process in OSS Communities: The Future AI Mentor
Xin Tan, Xiao Long, Yinghao Zhu +3
Onboarding newcomers is vital for the sustainability of open-source software (OSS) projects. To lower barriers and increase engagement, OSS projects have dedicated experts who prov…
FairEval: Evaluating Fairness in LLM-Based Recommendations with Personality Awareness
Chandan Kumar Sah, Xiaoli Lian, Tony Xu +1
Recent advances in Large Language Models (LLMs) have enabled their application to recommender systems (RecLLMs), yet concerns remain regarding fairness across demographic and psych…