Integrating AI-Driven Refactoring Tools with Human Expertise: A Java Development Perspective - Sai Bhargav Musuluri, (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024)
This article explores integrating AI-driven refactoring tools with human expertise in Java development environments, examining the evolution from traditional code maintenance to modern intelligent systems. The article discusses how artificial intelligence and machine learning capabilities enhance code refactoring processes while maintaining the crucial balance of human oversight. This article demonstrates the transformative impact of AI-assisted refactoring on software development practices by analyzing various implementation strategies, collaboration frameworks, and real-world case studies. The article highlights significant improvements in code quality, development efficiency, and team productivity by systematically applying AI-driven tools. Additionally, it examines the challenges and solutions in implementing these systems, particularly focusing on preserving business logic and managing technical debt. The article provides comprehensive insights into best practices for tool adoption, workflow integration, and quality control mechanisms while also exploring future trends in AI-driven development and their potential impact on software engineering practices.
Keywords: AI-Driven Refactoring; Java Development; Human-AI Collaboration; Code Quality Optimization; Software Maintenance Automation