11 papers · 1 filter
AI Policies: Help or Hindrance? A Software Developer's Perspective
Samuel Ferino, Rashina Hoda, John Grundy +2
AI policies introduced by software organisations to mitigate LLM-related risks such as sensitive information leaks and unauthorised usage are not useful if software developers do n…
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…
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…
Accountable Agents in Software Engineering: An Analysis of Terms of Service and a Research Roadmap
Christoph Treude
AI coding assistants and autonomous agents are becoming integral to software development workflows, reshaping how code is produced, reviewed, and maintained. While recent research…
Towards an Appropriate Level of Reliance on AI: A Preliminary Reliance-Control Framework for AI in Software Engineering
Samuel Ferino, Rashina Hoda, John Grundy +1
How software developers interact with Artificial Intelligence (AI)-powered tools, including Large Language Models (LLMs), plays a vital role in how these AI-powered tools impact th…
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…
"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…
GenAI Is No Silver Bullet for Qualitative Research in Software Engineering
Neil A. Ernst, Christoph Treude
Qualitative research gives rich insights into the quintessentially human aspects of software engineering as a socio-technical system. Qualitative research spans diverse strategies…
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…
Novice Developers' Perspectives on Adopting LLMs for Software Development: A Systematic Literature Review
Samuel Ferino, Rashina Hoda, John Grundy +1
Following the rise of large language models (LLMs), many studies have emerged in recent years focusing on exploring the adoption of LLM-based tools for software development by novi…