Enterprise-Scale COBOL-to-Java Translation: LLMs Augmented with Program Analysis

Modern enterprise systems often rely on legacy COBOL applications whose rigid, monolithic structure and globally scoped variables impede maintainability and cloud-native adoption. In this paper, we present a hybrid COBOL‑to‑Java translation pipeline that combines static program analysis with large language models (LLMs) to deliver scalable, consistent, and idiomatic Java code at enterprise scale. This translation pipeline is a core component of IBM's watsonx Code Assistant for Z (WCA for Z) product. Our Class Designer and Method Designer modules perform global analysis to infer Java classes, hierarchies, and method signatures from COBOL data divisions and control‑flow graphs, generating metadata that guides the LLM‑based translation of procedural logic.

We evaluate our pipeline on 20 GenAPP programs and 10 proprietary customer applications, comparing it against three standalone LLMs using an automated LLM‑as‑Judge framework. We show that our translation pipeline delivers a typical (median) structural quality score of over 80% and a functional score above 75%, while also reducing variability in results and enforcing uniform naming and design across all modules. Our translation pipeline, deployed across numerous client environments as part of IBM's WCA for Z, provides a cost-effective solution for application modernization—bridging the COBOL skills gap and accelerating enterprise-wide transformation.