The results show that AI effectively lowers cognitive barriers by summarizing pull requests, detecting minor localized errors, and helping developers discover system-level problems, but AI tools must adopt a "do more with less" design philosophy where the design should focus on high-reliability features and not overload the users with information.
Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to understand. Developers struggle to assess the validity of LLM-generated reviews, making it difficult to gauge how much trust to place in them. The role of Explainable AI (XAI)...
Zhenhan Gao, Marvin Muñoz Barón, Umm E. Habiba et al.· arXiv.org· 0 citations
The results show that agent-involved collaboration patterns, especially reviews initiated by AI agents or involving multiple AI agents, are associated with faster review decisions under Gradual AI Adoption and Rapid AI Agent Adoption, but these efficiency gains do not translate into better review quality.
Suzhen Zhong, Shayan Noei, Bram Adams et al.· 2 citations
AI-assisted development tools enable software engineers to generate implementations at substantially higher speed and volume than in traditional workflows, yet relatively little is known about how existing guardrails evolve in response.
A student survey study is presented that examines perceptions of LLM output understanding, validation effort, trust and the perceived usefulness of vibe modeling across several AI-assisted development scenarios to inform future studies for trustworthy and explainable AI-based software engineering via vibe modeling.
Shalini Chakraborty, M. Mittermaier, Judith Michael· arXiv.org· 0 citations
A structured human-in-the-loop architecture that reframes heuristic evaluation as a problem of cognitive labor distribution is proposed and produced heuristic evaluation results that showed substantially greater alignment with human experts than those generated by the automated baseline.
Hyeonyeong Lee, Dusan Baek, Woojin Park· Proceedings of the Human Fac...· 0 citations
It is concluded that GenAI, when implemented with clear guardrails and institutional integrity, has the potential to elevate advancement from an operational function to a strategic, mission-aligned partner in shaping the future of higher education.
Liz Hawkins· Journal of Education Advance...· 0 citations
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