Automating documentation and legacy code modernization: Revitalizing legacy systems with AI

Surendra, Praveen Kumar Manchikoni (2025) Automating documentation and legacy code modernization: Revitalizing legacy systems with AI. World Journal of Advanced Engineering Technology and Sciences, 15 (1). pp. 1390-1397. ISSN 2582-8266

This article examines how artificial intelligence technologies are revolutionizing the maintenance and modernization of legacy software systems in large organizations. Legacy systems, despite their outdated architectures, continue to power critical business operations while posing significant challenges due to poor documentation, obsolete programming paradigms, and the loss of original developer knowledge. The article demonstrates how AI-driven solutions address these challenges through automated documentation generation and code modernization strategies. These technologies enable comprehensive system understanding through semantic code analysis, facilitate incremental modernization through intelligent refactoring, and reduce risks through automated test generation. By implementing hybrid human-AI workflows and following incremental modernization strategies, organizations can transform aging codebases into well-documented, maintainable systems while avoiding the pitfalls of complete rewrites. The economic benefits include reduced maintenance costs, improved system agility, faster time-to-market, and enhanced developer productivity, making AI-assisted modernization a strategic imperative for organizations seeking to remain competitive in rapidly evolving markets.