A publicly released dataset of 15,591 configuration artifacts for five agentic AI coding tools, drawn from 4,738 GitHub repositories along with associated files and AI-co-authored commits.
AIDev: Studying AI Coding Agents on GitHub,
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2026 4roles
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The central challenge in AI-augmented CI/CD is designing authority transfer from humans to agents under constraints, as current systems remain limited to bounded data-plane autonomy backed by external governance.
Empirical analysis of AI refactoring PRs shows quality attribute improvements in 22.5% of cases with new Pylint issues in 24.17% and Bandit findings in 4.7%, yet 73.5% developer acceptance.
Agentic Agile-V uses Agile-V as backbone and a Specify-Constrain-Orchestrate-Prove-Evolve-Verify loop to convert AI agent conversations into traceable engineering artifacts with acceptance evidence.
citing papers explorer
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A Dataset of Agentic AI Coding Tool Configurations
A publicly released dataset of 15,591 configuration artifacts for five agentic AI coding tools, drawn from 4,738 GitHub repositories along with associated files and AI-co-authored commits.
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From Assistance to Agency: Rethinking Autonomy and Control in CI/CD Pipelines
The central challenge in AI-augmented CI/CD is designing authority transfer from humans to agents under constraints, as current systems remain limited to bounded data-plane autonomy backed by external governance.
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Quality and Security Signals in AI-Generated Python Refactoring Pull Requests
Empirical analysis of AI refactoring PRs shows quality attribute improvements in 22.5% of cases with new Pylint issues in 24.17% and Bandit findings in 4.7%, yet 73.5% developer acceptance.
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Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development
Agentic Agile-V uses Agile-V as backbone and a Specify-Constrain-Orchestrate-Prove-Evolve-Verify loop to convert AI agent conversations into traceable engineering artifacts with acceptance evidence.