9 citations · 17 across the 16 of their papers we have counts for
8 papers · 1 filter
Weaponizing the Commons: A Taxonomy and Detection Framework of Abuse on GitHub
Yuli Cheng, Xiaoyu Zhang, Jiongchi Yu +3
GitHub plays a critical role in modern software supply chains, making its security an important research concern. Existing studies have primarily focused on CI/CD automation, colla…
Where Agent Frameworks Fall Short: Examining Functional Challenges and Usability Concerns
Xinxue Zhu, Yanzhou Mu, Xiaoyu Zhang +5
Large language model (LLM) agents are increasingly built on agent frameworks that provide reusable abstractions for workflow orchestration, state management, tool integration, and…
ASSURE: Metamorphic Testing for AI-powered Browser Extensions
Xuanqi Gao, Juan Zhai, Shiqing Ma +2
The integration of Large Language Models (LLMs) into browser extensions has revolutionized web browsing, enabling sophisticated functionalities like content summarization, intellig…
The Invisible Hand: Unveiling Provider Bias in Large Language Models for Code Generation
Xiaoyu Zhang, Juan Zhai, Shiqing Ma +5
Large Language Models (LLMs) have emerged as the new recommendation engines, surpassing traditional methods in both capability and scope, particularly in code generation. In this p…
Efficient DNN-Powered Software with Fair Sparse Models
Xuanqi Gao, Weipeng Jiang, Juan Zhai +3
With the emergence of the Software 3.0 era, there is a growing trend of compressing and integrating large models into software systems, with significant societal implications. Regr…
CITADEL: Context Similarity Based Deep Learning Framework Bug Finding
Xiaoyu Zhang, Juan Zhai, Shiqing Ma +2
With the application of deep learning technology, tools of DL framework testing are in high demand. Existing DL framework testing tools have limited coverage of bug types. For exam…
From Effectiveness to Efficiency: Uncovering Linguistic Bias in Large Language Model-based Code Generation
Weipeng Jiang, Xuanqi Gao, Juan Zhai +4
Large Language Models (LLMs) have demonstrated promising capabilities for code generation. While existing benchmarks evaluate the correctness and efficiency of LLM-generated code,…
DREAM: Debugging and Repairing AutoML Pipelines
Xiaoyu Zhang, Juan Zhai, Shiqing Ma +1
Deep Learning models have become an integrated component of modern software systems. In response to the challenge of model design, researchers proposed Automated Machine Learning (…