arXiv2026
Mainframe systems continue to support critical applications across industries such as banking, retail, and healthcare. Exposing their functionality through Application Programming Interfaces (APIs) enables reuse and development of new applications, but identifying and implementing APIs for legacy code remains challenging. It requires understanding complex programs, separating dependent components, introducing new artifacts, and preserving functionality and Service Level Agreements (SLAs) such as Turnaround Time (TAT). We propose a framework for APIfication of legacy mainframe applications. Candidate APIs are identified from artifacts such as transactions, screens, control-flow blocks, inter-microservice calls, business rules, and data accesses. Static analyses, including liveness and reaching definitions, are then used to traverse the code and automatically compute API signatures consisting of request and response fields. We evaluated the framework through a qualitative survey of nine mainframe developers with an average of 15 years of experience, using the public GENAPP application and two industrial mainframe applications. The results show that the framework identifies additional candidate APIs and reduces implementation effort for APIfication. The API-signature computation has been incorporated into IBM watsonx Code Assistant for Z Refactoring Assistant. We further validated the identified APIs by executing them on an IBM Z mainframe system, demonstrating the practical viability of the approach.