Generative AI for Automated Code Generation: ...

Generative AI for Automated Code Generation: Transforming Software Development and Maintenance

Author Name : Nidhi Khot

ABSTRACT Generative AI is transforming the landscape of software development and maintenance by introducing innovative automated code generation technologies. This paper explores the capabilities of advanced models, such as OpenAI’s Codex and GitHub Copilot, in revolutionizing traditional software development practices. These models leverage extensive datasets of publicly available code to generate meaningful code snippets and entire functions from minimal user inputs. The introduction of generative AI not only streamlines the coding process but also enhances overall productivity by reducing the time developers spend on repetitive and mundane tasks. Furthermore, generative AI contributes significantly to code refactoring, automated testing, and bug detection, ensuring that the software produced is of high quality and adheres to industry standards. However, the integration of these technologies into software development is not without challenges. Issues such as code quality, security vulnerabilities, and ethical considerations surrounding copyright and ownership of AI-generated code remain critical concerns. As generative AI continues to evolve, it is reshaping the roles and responsibilities of software developers, shifting their focus from routine coding to overseeing AI-generated outputs and ensuring their reliability and security. This paper aims to provide a comprehensive overview of these advancements, the challenges they present, and their implications for the future of software engineering.