AI-Powered Software Engineering: Integrating Advanced Techniques for Optimal Development

This paper delves into the integration of Artificial Intelligence (AI) within the software engineering lifecycle, examining its transformative effects on coding, testing, and maintenance. The study identifies specific improvements brought about by AI, such as enhanced efficiency and accuracy in coding, improved testing processes through automated test case generation and defect prediction, and effective maintenance strategies using AI-driven bug fixing and refactoring. However, it also highlights significant challenges, including data quality, model explainability, and integration with existing processes. By providing a comprehensive analysis of AI’s role across various stages of software development, this paper aims to bridge existing research gaps and offer practical strategies for real-world applications. Future research directions are suggested to explore AI’s potential in design and requirements analysis phases and to develop robust, explainable AI models tailored for software engineering. The findings underscore the transformative potential of AI in software engineering and the need for collaborative efforts to address integration challenges.