Software engineering is evolving rapidly due to advancements in Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs). Traditional software development processes are highly dependent on manual effort across requirement analysis, design, coding, testing, deployment, and maintenance, making them time-consuming and error-prone. Recent AI technologies have demonstrated the ability to automate several phases of the software development lifecycle, significantly improving productivity and software quality. This paper proposes a comprehensive Intelligent Software Engineering Framework that integrates Generative AI, machine learning, automated testing, security validation, and continuous learning mechanisms into a unified system. The proposed framework enables automated requirement understanding, intelligent code generation, automated testing, vulnerability detection, documentation generation, and deployment support. The framework enhances efficiency, reduces development time, improves software reliability, and supports continuous improvement through feedback-driven learning.
Dr> Surender Singh (Thu,) studied this question.