5 citations · 13 across the 15 of their papers we have counts for
18 papers
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…
EVOMAL: Self-Poisoning in Self-Evolving Coding Agents
Xiaodong Wu, Yu Shi, Qi Li +5
Self-evolving LLM coding agents write their own tools by imitating retrieved skills from shared skill libraries. We identify a vulnerability in this loop: during authoring, a retri…
Turning Interaction History into Execution State: A Runtime Layer for Long-Horizon Coding Agents
Zehao Wang, Yisen Xu, Chenglin Li +5
Long-horizon coding agents accumulate hundreds of actions and observations in their trajectories, yet nothing in this record indicates which observations still describe the reposit…
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…
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…
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…
Agentic Refactoring: An Empirical Study of AI Coding Agents
Kosei Horikawa, Hao Li, Yutaro Kashiwa +3
Agentic coding tools, such as OpenAI Codex, Claude Code, and Cursor, are transforming the software engineering landscape. These AI-powered systems function as autonomous teammates…
Agent READMEs: An Empirical Study of Context Files for Agentic Coding
Worawalan Chatlatanagulchai, Hao Li, Yutaro Kashiwa +8
Agentic coding tools receive goals written in natural language, break them down into specific tasks, and write or execute code with minimal human intervention. Central to this proc…
Building an Open AIBOM Standard in the Wild
Gopi Krishnan Rajbahadur, Keheliya Gallaba, Elyas Rashno +4
Modern software engineering increasingly relies on open, community-driven standards, yet how such standards are created in fast-evolving domains like AI-powered systems remains und…
On the Use of Agentic Coding: An Empirical Study of Pull Requests on GitHub
Miku Watanabe, Hao Li, Yutaro Kashiwa +3
Large language models (LLMs) are increasingly being integrated into software development processes. The ability to generate code and submit pull requests with minimal human interve…
Understanding Prompt Management in GitHub Repositories: A Call for Best Practices
Hao Li, Hicham Masri, Filipe R. Cogo +3
The rapid adoption of foundation models (e.g., large language models) has given rise to promptware, i.e., software built using natural language prompts. Effective management of pro…
From Hugging Face to GitHub: Tracing License Drift in the Open-Source AI Ecosystem
James Jewitt, Hao Li, Bram Adams +2
Hidden license conflicts in the open-source AI ecosystem pose serious legal and ethical risks, exposing organizations to potential litigation and users to undisclosed risk. However…
Agentic Software Engineering: Foundational Pillars and a Research Roadmap
Ahmed E. Hassan, Hao Li, Dayi Lin +4
Agentic Software Engineering (SE 3.0) represents a new era where intelligent agents are tasked not with simple code generation, but with achieving complex, goal-oriented SE objecti…
On the Effect of Token Merging on Pre-trained Models for Code
Mootez Saad, Hao Li, Tushar Sharma +1
Tokenization is a fundamental component of language models for code. It involves breaking down the input into units that are later passed to the language model stack to learn high-…
Model Context Protocol (MCP) at First Glance: Studying the Security and Maintainability of MCP Servers
Mohammed Mehedi Hasan, Hao Li, Emad Fallahzadeh +3
Although Foundation Models (FMs), such as GPT-4, are increasingly used in domains like finance and software engineering, reliance on textual interfaces limits these models' real-wo…
Can We Recycle Our Old Models? An Empirical Evaluation of Model Selection Mechanisms for AIOps Solutions
Yingzhe Lyu, Hao Li, Heng Li +1
AIOps (Artificial Intelligence for IT Operations) solutions leverage the tremendous amount of data produced during the operation of large-scale systems and machine learning models…
Towards Refining Developer Questions using LLM-Based Named Entity Recognition for Developer Chatroom Conversations
Pouya Fathollahzadeh, Mariam El Mezouar, Hao Li +2
In software engineering chatrooms, communication is often hindered by imprecise questions that cannot be answered. Recognizing key entities can be essential for improving question…
Software Engineering and Foundation Models: Insights from Industry Blogs Using a Jury of Foundation Models
Hao Li, Cor-Paul Bezemer, Ahmed E. Hassan
Foundation models (FMs) such as large language models (LLMs) have significantly impacted many fields, including software engineering (SE). The interaction between SE and FMs has le…