Navigating The Challenges Of Integrating AI Guidance Into Complex And Legacy Codebases

Author: Abas Kadar

Journal: SSRN : Social Science Research Network, 2024

Abstract: The integration of artificial intelligence (AI) into software development processes has become a significant trend, promising to enhance productivity, code quality, and decision-making. However, applying AI-based guidance to complex and legacy codebases presents several unique challenges. These challenges stem from issues such as code structure, technical debt, outdated frameworks, and a lack of standardized documentation. Legacy systems, often built with older programming languages or obsolete tools, can make the seamless implementation of AI tools and frameworks more difficult. This article explores these challenges in depth and offers practical solutions for overcoming them. By examining the key obstacles-such as dealing with unstructured code, understanding legacy architecture, and ensuring AI models' adaptability-this research provides a roadmap for developers and organizations looking to leverage AI in maintaining and evolving their legacy systems. Ultimately, it aims to provide insights on how AI guidance can be effectively integrated into existing codebases to improve long-term development efficiency, scalability, and code quality.

Keywords: AI-guided development, Software development, Technical debt, Legacy codebases, AI integration

DOI / Source: https://doi.org/10.2139/ssrn.5150449

License: Creative Commons Attribution 4.0