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publications

An Empirical Study of Yanked Releases in the Rust Package Registry

Published in IEEE Transactions on Software Engineering (TSE), 2023

Empirical study investigating yanked releases in the Rust package ecosystem, analyzing patterns and impacts on software reliability and dependency management.

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The Rise of AI Teammates in Software Engineering (SE) 3.0: How Autonomous Coding Agents Are Reshaping Software Engineering

Published in arXiv, 2024

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Agentic Software Engineering: Foundational Pillars and a Research Roadmap

Published in arXiv, 2024

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Keeping Deep Learning Models in Check: A History-Based Approach to Mitigate Overfitting

Published in IEEE Access, 2024

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Bridging the language gap: an empirical study of bindings for open source machine learning libraries across software package ecosystems

Published in Empirical Software Engineering (EMSE), 2024

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Studying the Impact of TensorFlow and PyTorch Bindings on Machine Learning Software Quality

Published in ACM Transactions on Software Engineering and Methodology (TOSEM), 2024

Empirical study examining how TensorFlow and PyTorch bindings affect machine learning software quality across different programming languages.

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Understanding Prompt Management in GitHub Repositories: A Call for Best Practices

Published in IEEE Software, 2025

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A Systematic Literature Review of Software Engineering Research on Jupyter Notebook

Published in Journal of Systems and Software (JSS), 2025

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From Hugging Face to GitHub: Tracing License Drift in the Open-Source AI Ecosystem

Published in arXiv, 2025

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HAFixAgent: History-Aware Automated Program Repair Agent

Published in arXiv, 2025

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Agentic Refactoring: An Empirical Study of AI Coding Agents

Published in arXiv, 2025

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Agent READMEs: An Empirical Study of Context Files for Agentic Coding

Published in arXiv, 2025

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SwarmUpdate: Hierarchical Software Updates and Deep Learning Model Patching for Heterogeneous UAV Swarms

Published in arxiv, 2025

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Software Engineering and Foundation Models: Insights from Industry Blogs Using a Jury of Foundation Models

Published in 2025 IEEE/ACM 47th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP), 2025

Research on software engineering and foundation models using industry blog analysis with LLM jury approach for comprehensive insights.

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

Published in arxiv, 2026

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Hao Li

Posts by Collection

portfolio

publications

An Empirical Study of Yanked Releases in the Rust Package Registry

The Rise of AI Teammates in Software Engineering (SE) 3.0: How Autonomous Coding Agents Are Reshaping Software Engineering

Agentic Software Engineering: Foundational Pillars and a Research Roadmap

Keeping Deep Learning Models in Check: A History-Based Approach to Mitigate Overfitting

Bridging the language gap: an empirical study of bindings for open source machine learning libraries across software package ecosystems

Studying the Impact of TensorFlow and PyTorch Bindings on Machine Learning Software Quality

Understanding Prompt Management in GitHub Repositories: A Call for Best Practices

A Systematic Literature Review of Software Engineering Research on Jupyter Notebook

From Hugging Face to GitHub: Tracing License Drift in the Open-Source AI Ecosystem

HAFixAgent: History-Aware Automated Program Repair Agent

Agentic Refactoring: An Empirical Study of AI Coding Agents

Agent READMEs: An Empirical Study of Context Files for Agentic Coding

SwarmUpdate: Hierarchical Software Updates and Deep Learning Model Patching for Heterogeneous UAV Swarms

Software Engineering and Foundation Models: Insights from Industry Blogs Using a Jury of Foundation Models

An Empirical Study of Testing Practices in Open Source AI Agent Frameworks and Agentic Applications

Model Context Protocol (MCP) at First Glance: Studying the Security and Maintainability of MCP Servers

Beyond Blame: Rethinking SZZ with Knowledge Graph Search

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

Mind the Merge: Evaluating the Effects of Token Merging on Pre-trained Models for Code

Towards Refining Developer Questions using LLM-Based Named Entity Recognition for Developer Chatroom Conversations

On the Use of Agentic Coding: An Empirical Study of Pull Requests on GitHub

Can We Recycle Our Old Models? An Empirical Evaluation of Model Selection Mechanisms for AIOps Solutions

AIDev: Studying AI Coding Agents on GitHub

Do AI Coding Agents Log Like Humans? An Empirical Study

Permissive-Washing in the Open AI Supply Chain: A Large-Scale Audit of License Integrity

talks

Foundation Models and Software Engineering: Insights from Industry Blogs

Agentic Software Engineering: The Rise of AI Teammates

Agentic Software Engineering: A Roadmap to Software Engineering 3.0

Agentic Software Engineering: The Rise of AI Teammates

teaching