arXiv AI By Srinath Perera, Hasinthaka Piyumal, Frank Leymann, Rania Khalaf

A Methodology for Investigating AI Patterns Prevalence in Software Repositories

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arXiv:2607. 00558v1 Announce Type: cross Abstract: As Artificial Intelligence(AI)-based applications take off, a clear understanding of AI patterns can uplift the quality of AI applications.

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Rule Taxonomy and Evolution in AI IDEs: A Mining and Survey Study

arXiv:2606. 12231v1 Announce Type: cross Abstract: The adoption of AI-powered Integrated Development Environments (AI IDEs) has introduced "Rules" as a novel software artifact, allowing developers to persistently inject project-specific constraints and architectural guidelines into the context of Large Language Models (LLMs).

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Detecting AI Coding Agents in Open Source: A Validated Multi-Method Census of 180 Million Repositories

Generative AI coding agents are entering the open-source supply chain, yet their diverse and often invisible traces leave their prevalence poorly understood. We introduce a multi-layered detection framework that integrates configuration-file scanning, commit-message analysis, author-identity matching, and bot-signature lookup across World of Code (180M+ Git repositories), classifying agent traces into four behavioral types.