Automated Code Analysis Services for Host COBOL Application for large client in financial sector

Automated code analysis for COBOL batch jobs classified as top mainframe CPU consumers and as champions in execution duration, aiming at the discovery of a) candidate CPU intensive code patterns/blocks and b) long running code patterns/blocks within the programs.

Τhe Customer

The client is a European leader in the design, creation and management of technology infrastructures and services for Financial Institutions, Central Banks, Corporates and the Public Sector, in the areas of Card & Merchant Solutions, Digital Payment Solutions and Capital Market & Network Solutions. It provides its services in 50 countries and operates through its subsidiaries, and representation offices in more than ten countries around the globe.


Our client used a legacy, in-house developed, mainframe COBOL application with millions of lines of code. The need emerged since 2015 with the constant increase of transaction volumes serviced by the specific application: both the  mainframe CPU consumption of the batch programs/jobs and the duration of the long running batch jobs had to be reduced to fit in the time window of the daily runs.


The automated code analysis was performed with the use of TOTEM Code Analysis Tool developed by Uni Systems. With this assignment, our client had the opportunity to use an effective, tool-based methodology for code analysis, which can be used for the discovery of various application code aspects, such as code quality, legacy code parts for modernization and CPU intensive code patterns. This methodology can address the needs of organizations maintaining applications with millions of Lines of Code (LOCs).


The outcome of the automated code analysis was used to our client in order to do targeted code modifications/optimizations in the analyzed programs, resulting in the reduction of their mainframe CPU consumption and/or of their execution duration. So with this assignment the New SIA Host Application could manage the increasing transaction volumes and the cost of the mainframe resources.