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Successful COBOL mainframe modernization requires two distinct phases: reverse engineering (understanding what existing systems do) and forward engineering (building new applications). AI coding assistants excel at the second phase but need proper context for the first. Key requirements include bounded and complete dependency resolution, platform-aware context (compiler/runtime behavior not visible in source code), and traceable outputs for regulatory compliance. AWS Transform addresses this by building a deterministic model of the entire application landscape before AI gets involved, decomposing programs into bounded units, and validating every AI output against deterministic evidence. Real-world results include BMW Group reducing testing time by 75%, Fiserv completing a 29-month project in 17 months, and Itau cutting discovery and testing time by over 90%.

Learnings from COBOL modernization in the real world

What a successful mainframe modernization requires