California DMV Modernizes Legacy Codebase with IBM Watsonx.ai
The California Department of Motor Vehicles (DMV) needed to modernize its systems to provide digital, self-service experiences for millions of Californians. However, decades of embedded business logic in legacy code made it challenging to understand and update the systems. The DMV relied on aging technology with a core architecture built in the late 1970s that depended on mainframe applications written in COBOL and Assembler.
To regain an understanding of its COBOL and Assembly codebases, the DMV brought in IBM Consulting, IBM Analysis and Renovation Catalyst (ARC), and IBM Watsonx.ai. The partnership used a flexible platform to deliver cutting-edge DMV services to millions of Californians. The modernization problem was hiding inside working code, with business rules locked inside decades-old code.
The DMV needed to extract and validate the business rules embedded across roughly 6 million lines of code spanning 2500 COBOL and Assembler programs. Manual extraction was impractical due to limited access to expert programmers and the risk of regression across related modules, batch jobs, partners, and downstream systems.
The IBM approach used ARC and Watsonx.ai to analyze mainframe and legacy application code. ARC performed static analysis on COBOL and Assembler programs to identify structure, dependencies, variables, conditional logic, and business-rule patterns. The outputs included size and complexity metrics, program call chains, pseudocode, business rule summaries, and logical flow diagrams.
The pipeline produced spreadsheet-based outputs that combined original code snippets, pseudocode, and Watsonx.ai-generated summaries. Human validation remained a nonnegotiable part of the process, with AI-generated drafts reviewed by IBM mainframe experts and DMV subject matter experts for policy and regulatory accuracy.