Automated Code Review and Bug Detection

With the increasing demand for efficient code reviews, especially among beginner programmers, existing tools often lack user-friendliness and fail to streamline error detection and correction effectively. To address these gaps, this paper presents an Automated Code Review and Bug Detection Tool designed to simplify the identification and fixing of code errors. The tool features an intuitive graphical user interface (GUI) tailored for both novice and experienced programmers. Leveraging advanced machine learning models, it classifies errors and suggests code refinements, ensuring accurate and efficient error detection. The development process involved integrating machine learning algorithms for error classification within a streamlined GUI. Usability and effectiveness were assessed through feedback from 21 participants, highlighting the tool's capability to enhance programming accessibility and simplify the review process. The successful implementation demonstrates the tool's potential to provide a user-friendly solution, contributing to more efficient programming practices and making code review accessible to a broader audience.