Designing Enterprise-Wide Code Modernization Strategies for Quant, AI, and Engineering Systems
DOI:
https://doi.org/10.54741/ASEJAR/4.2.2025.181Keywords:
enterprise software modernization, code refactoring, architecture modernization, quant systems, AI systems, engineering systems, performance optimization, maintainability, reliability, cloud and GPU integrationAbstract
Monolithic, performance-sensitive, and challenging-to-maintain legacy codebases can cause problems for enterprise software systems in the engineering, quantitative, and artificial intelligence (AI) domains. This study proposes a hypothetical enterprise-wide code modernization methodology that combines code-level refactoring, architecture modernization, and infrastructure changes to enhance system efficiency, maintainability, and reliability. Using scenario-based evaluations, the study examines the effectiveness of resource consumption, the reduction of execution time, and the rates of adoption of modernization strategies across different types of systems. The results demonstrate that AI systems benefit from modularization and GPU acceleration, engineering systems have significant advances in dependability and maintainability, and quant systems benefit most from performance optimizations. The findings emphasize the importance of system-specific modernization solutions within a structured, layered architecture, supported by governance and risk management, in order to transform outdated systems into scalable and future-ready platforms.
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Copyright (c) 2025 Jay Dalal
This work is licensed under a Creative Commons Attribution 4.0 International License.
Research Articles in 'Applied Science and Engineering Journal for Advanced Research' are Open Access articles published under the Creative Commons CC BY License Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/. This license allows you to share – copy and redistribute the material in any medium or format. Adapt – remix, transform, and build upon the material for any purpose, even commercially.
