Abstract
Code review has been a well-established quality assurance strategy in software engineering. Nowadays, code review is a tool-based practice, a potential scenario for tools based on generative artificial intelligence (AI) models, which have recently gained worldwide popularity. Initial evidence has shown these tools may support reviewers checking a code change and overcoming understanding barriers, among other possibilities. A way to map potential future directions of tool support is to understand practitioners’ perceptions. In this study, we investigate what has been discussed about generative AI in the code review context by performing a gray literature review. We analyzed 42 documents and found insights from practice and proposals of solutions using generative AI models. Our study provides evidence of code review practitioners actively exploring this new technology, especially ChatGPT. We also discuss three potential implications: saving time, understanding changes, and reviewability of code changes.