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cs.SE2026

On the Maintenance and Co-evolution of Agent Plugins: An Empirical Study of Claude Code Plugin Marketplaces

Ahmed Hereiz, Yingzhe Lyu, Hao Li +2

AI coding agents, software tools that automate development tasks through reasoning and tool use, are increasingly extended through plugin marketplaces, yet the structure, maintenan…

cs.SE2026

Don't Trust the Label: License Laundering in AI Supply Chains

James Jewitt, Hao Li, Gopi Krishnan Rajbahadur +2

AI artifacts move through a multi-platform supply chain, spanning datasets and models on Hugging Face and applications on GitHub. While each artifact carries a license whose obliga…

cs.SE2026

Don't Blame the Large Language Model: How Agent Harness Evolution Shapes Coding Agent Quality

Oussama Ben Sghaier, Hao Li, Bram Adams +1

Coding agents, autonomous systems that use large language models (LLMs) to resolve software engineering tasks, rely on agent harness: a middleware layer in between a developer and…

cs.SE2026

AIDev: Studying AI Coding Agents on GitHub

Hao Li, Haoxiang Zhang, Ahmed E. Hassan

AI coding agents are rapidly transforming software engineering by performing tasks such as feature development, debugging, and testing. Despite their growing impact, the research c…

cs.SE2026

Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions

Mohammed Mehedi Hasan, Hao Li, Gopi Krishnan Rajbahadur +2

The Model Context Protocol (MCP) introduces a standard specification that defines how Foundation Model (FM)-based agents should interact with external systems by invoking tools. Ho…

cs.SE2026

AgenticSZZ: Temporal Knowledge Graph-Guided Agentic Bug-Inducing Commit Identification

Yu Shi, Hao Li, Bram Adams +1

Identifying Bug-Inducing Commits (BICs) is fundamental for understanding software defects and enabling downstream tasks such as defect prediction and automated program repair. Yet…