5 citations · 13 across the 15 of their papers we have counts for
11 papers · 1 filter
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…