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

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 Legacy systems, despite their outdated architectures, continue to power critical business operations while posing significant challenges due to poor documentation, obsolete programming paradigms,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.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-04-20
DOI
https://doi.org/10.30574/wjaets.2025.15.1.0367
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Praveen Kumar Manchikoni Surendra
World Journal of Advanced Engineering Technology and Sciences
Scientific Computing and Data Management
article

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

Praveen Kumar Manchikoni Surendra
article en

Abstract

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 Legacy systems, despite their outdated architectures, continue to power critical business operations while posing significant challenges due to poor documentation, obsolete programming paradigms,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.

World Journal of Advanced Engineering Technology and SciencesVol. 15(1)
Openalex Percentile: Top 91%
Scientific Computing and Data Management
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