A Review on Role of Generative AI in Software Development
A Review on Role of Generative AI in Software Development
Authors:
Dr. Suresh Kurumalla¹, Dr. Kasa Ravindra2, Kola Venkata Abhinay²
¹Professor, Department of Computer Science and Engineering, St. Martin’s Engineering College, Hyderabad, India, kurumallasuresh@gmail.com
2Professor&Director, Department of Electronics and Communication Engineering,
St. Martin’s Engineering College, Hyderabad, India,drkasaravindra@gmail.com
3Student, Department of Computer Science and Engineering, St. Martin’s Engineering College, Hyderabad, India ,venkatabhinay60@gmail.com
Abstract
The rapid advancement of generative artificial intelligence has significantly transformed software development processes, introducing new levels of automation, efficiency, and innovation. In modern development environments, the demand for faster delivery, high-quality code, and scalable solutions has driven the adoption of AI-powered tools. This review explores the role of generative AI in software development, focusing on its applications in code generation, debugging, testing, documentation, and system design. The study examines various generative models, including transformer-based architectures, and analyzes their integration into development workflows through tools such as AI copilots and automated assistants. It also evaluates performance improvements, productivity gains, and the impact on developer experience. Furthermore, the review highlights challenges such as code reliability, security vulnerabilities, ethical concerns, and over-dependence on AI systems. The findings indicate a growing shift toward human-AI collaborative development, where generative AI enhances but does not replace human expertise. The paper concludes by identifying future research directions, including improving contextual understanding, ensuring responsible AI usage, and developing domain-specific generative models to support robust and efficient software engineering practices.
Keywords: Generative Artificial Intelligence, Software Development, Code Generation, AI Copilots, Automated Testing, Software Engineering, Transformer Models, Human-AI Collaboration, AI-assisted Programming, Intelligent Development Systems.