The utilization of Large Language Models for code review represents a promising direction in enhancing software quality and development practices. This paper discusses the efficiencies and potential implications of a LLM-driven approach to improving code review processes and software education.

• Main Points:
  • Use of LLMs for detecting bugs, code smells, and suggesting improvements.
  • Predictive capabilities of these models in identifying future risks in code.
  • Contributions to the dual goals of enhancing code quality and developer education.

This research highlights the transformative potential of integrating advanced AI models into software development, offering significant improvements and educational benefits for developers, shaping the future landscape of software engineering.