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Code Reborn AI-Driven Legacy Systems Modernization from COBOL to Java

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arxiv 2504.11335 v1 pith:LVOYZFLE submitted 2025-04-15 cs.SE cs.AIcs.LG

Gopichand Bandarupalli This is my paper · ORCID
classification cs.SEcs.AIcs.LG
keywords cobolcodejavalegacysystemsai-drivenmodernizationaccuracy
verification ladder T0 review T1 audit T2 compute T3 formal
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This study investigates AI-driven modernization of legacy COBOL code into Java, addressing a critical challenge in aging software systems. Leveraging the Legacy COBOL 2024 Corpus -- 50,000 COBOL files from public and enterprise sources -- Java parses the code, AI suggests upgrades, and React visualizes gains. Achieving 93% accuracy, complexity drops 35% (from 18 to 11.7) and coupling 33% (from 8 to 5.4), surpassing manual efforts (75%) and rule-based tools (82%). The approach offers a scalable path to rejuvenate COBOL systems, vital for industries like banking and insurance.

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Cited by 3 Pith papers

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    cs.CR 2025-05 reject novelty 3.0 of 10

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  3. The Impact of Software Testing with Quantum Optimization Meets Machine Learning

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