arXiv:2605. 17548v2 Announce Type: replace-cross Abstract: Code review has evolved for decades, from informal peer checking to today's pull request (PR) workflows, yet it remains a largely manual and cognitively demanding process.
By H\"useyin \"Ozg\"ur Kamal{\i}, Erdem Tuna, Vahid Haratian, Eray T\"uz\"un
arXiv:2607. 29516v1 Announce Type: cross Abstract: AI coding agents are generating code at volumes that exceed the capacity of traditional peer review.
By Chandra Maddila, Mashrur Rashik, Euna Mehnaz Khan, Smriti Jha, James Saindon, Nachi Nagappan, Peter C. Rigby
arXiv:2607. 01867v1 Announce Type: cross Abstract: The use of LLMs in software development has become increasingly widespread on tasks such as code generation and summarization.
By Yongyi Ji, Jiaji Wang, Yi Zhou, Fuxiang Chen, Hongji Yang
The use of LLMs in software development has become increasingly widespread on tasks such as code generation and summarization. Reports from large technology companies showed that around 20% to 30% of their code are generated by LLMs.
arXiv:2607. 03316v1 Announce Type: cross Abstract: Agentic code review, where autonomous agents provide code review comments on pull requests, is increasingly integrated into development workflows, yet there is limited empirical evidence on how developers respond to such comments in practice.
By Hong Yi Lin, Mingzhao Liang, Kla Tantithamthavorn, Patanamon Thongtanunam
arXiv:2609.37216v1 Announce Type: cross
Abstract: Large language models can generate plausible code-review comments, but such comments may contain technically incorrect claims that mislead developers...
By Yue Pan, Jiawei Li, Ziyuan Zhang, Xiangxin Zhao, He Ye