Integrating Generative AI into the Software Development Lifecycle: Impacts on Code Quality and Maintenance

Recent advances in generative AI have depicted it as a revolutionary approach in the software development technologies pioneered to improve the codes' reliability and sustain their quality and performance. Generative AI tools can help develop code independently, suggest intelligent solutions and ideas, and enhance several development procedures thanks to superior algorithms and machine learning features. This paper discusses how generative AI can/has been applied within software development to achieve the following three goals: First, to increase the code quality using automated code generation/review. Second, the code maintainability should be improved through standards and documentation. Third, to increase the up-to-speed development productivity due to AI-based automation, namely the automation of repetitive tasks and fast prototyping. The paper also considers issues and difficulties that can be tied to AI in this context: problems of dependence on AI, ethical and security issues, and technical imperfections. Finally, the implications of generative AI in software development in the future are presented, which can open a new direction in the development of software products while primarily pointing to the processes of managing the introduction of generative AI. Using the evaluation of the current possibilities and future perspectives of generative AI presented in this paper, one can conclude its impact on the future of software engineering.