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.
arXiv:2606. 24429v1 Announce Type: cross Abstract: Generative AI coding agents are entering the open-source supply chain, yet their diverse and often invisible traces leave their prevalence poorly understood.
By Arsham Khosravani, Audris Mockus
arXiv:2608. 00101v1 Announce Type: cross Abstract: AI coding agents like GitHub Copilot, Claude Code, and Codex interleave multi-step LLM inference with tool execution, creating a workload different from chatbots.
By Banruo Liu, Haoran Qiu, \'I\~nigo Goiri, Rodrigo Fonseca, Ricardo Bianchini, Esha Choukse
arXiv:2607. 14037v1 Announce Type: cross Abstract: Agentic coding tools are increasingly capable of generating and submitting pull requests (PRs) to software projects, introducing new forms of human-agent collaboration in software development.
By Maliha Noushin Raida, Daqing Hou
The study investigates how autonomous coding agents interact with technical documentation, analyzing 557 coding sessions and 33,097 pull requests. Findings reveal that agents primarily engage with agent-facing artefacts, show weak links between documentation consultation and code editing, lack explicit validation sequences, and tend to consult documentation after code changes. The authors propose a two‑lobed cycle model of agent‑documentation interaction and challenge assumptions about actionability and verifiability of agent‑friendly documentation.
Agentic coding tools are increasingly capable of generating and submitting pull requests (PRs) to software projects, introducing new forms of human-agent collaboration in software development. While prior studies have examined PR-level outcomes of agent-generated contributions, less is known about how agentic coding tools are adopted and managed at the project level.
arXiv:2608. 20195v1 Announce Type: cross Abstract: Technical documentation is written for human developers, but an increasing share of software changes is now authored by autonomous coding agents.
By Zhijun Gao, Jing Chen
arXiv:2607. 21832v1 Announce Type: cross Abstract: Recent advances in large language models and their rapid adoption across software engineering tasks have made Artificial Intelligence (AI) coding agents an integral component of modern software development workflows.
By Iren Mazloomzadeh, Mohammad Mehdi Morovati, Foutse Khomh
arXiv:2606. 08500v1 Announce Type: cross Abstract: Software engineering agents (SWE agents) increasingly work through tool-mediated trajectories in real repositories, yet their behavior remains difficult to characterize in concrete, observable terms.
By Zhengyi Zhuo, Yan Liu
arXiv:2603. 21489v2 Announce Type: replace-cross Abstract: AI agents have become increasingly capable at isolated software engineering (SWE) tasks such as resolving issues on Github.
By Jiayi Geng, Graham Neubig
arXiv:2608. 03585v1 Announce Type: new Abstract: Open-source software communities are a form of digital public infrastructure that not only produces code, but also generates public knowledge and interpersonal relationships through visible collaboration.
By Mengying Zhou, Yongjie Yin, Yang Chen
arXiv:2606. 13468v1 Announce Type: cross Abstract: AI coding agents are increasingly used to generate pull requests (PRs) that propose code fixes in software projects.
By Mahmoud Abujadallah, Ali Arabat, Mohammed Sayagh