10 papers
"An Endless Stream of AI Slop": How Developers Discuss the Burden of AI-Assisted Software Development
Sebastian Baltes, Marc Cheong, Christoph Treude
"AI slop", that is, low-quality AI-generated content, is increasingly affecting software development, from generated code and pull requests to documentation and bug reports. Howeve…
AI Slop and the Software Commons
Sebastian Baltes, Marc Cheong, Christoph Treude
In this article, we argue that AI slop in software is creating a tragedy of the commons. Individual productivity gains from AI-generated content externalize costs onto reviewer cap…
The Impact of Configuring Agentic AI Coding Tools on Build-vs-Buy Decisions: A Study Protocol
Jai Lal Lulla, Matthias Galster, Jie M. Zhang +2
Agentic AI coding tools write code with increasing autonomy and in doing so decide when to import a library and when to implement functionality from scratch. These decisions, wheth…
Walking the Tightrope of LLMs for Software Development: A Practitioners' Perspective
Samuel Ferino, Rashina Hoda, John Grundy +1
Background: Large Language Models emerged with the potential of provoking a revolution in software development (e.g., automating processes, workforce transformation). Although stud…
A Dataset of Agentic AI Coding Tool Configurations
Matthias Galster, Seyedmoein Mohsenimofidi, Levi Böhme +4
Agentic AI coding tools such as Claude Code and OpenAI Codex execute multi-step coding tasks with limited human oversight. To steer these tools, developers create repository-level…
Operationalizing Ethics for AI Agents: How Developers Encode Values into Repository Context Files
Christoph Treude, Sebastian Baltes, Marc Cheong
As AI coding agents become embedded in software development workflows, developers are beginning to operationalize ethical principles by encoding behavioral rules into repository-le…