Cost Saving with Quality Assurance – Customer Report

Recently a HORIZONT customer required a quality assurance (QA) system check of all processes of a large new application package before going productive.

This meant:

• Completely replicating the application (including all interfaces) in the QA system.

• Testing the modified processes over eleven production days in the QA system. To be able to recognize and resolve possible issues before the trial run, a JCL check was performed for the entire time frame.

The test focused on running a check of the application programs. This meant that production control had to make available all the elements required for running the application programs properly. “Unnecessary” issues such as JCL errors, checking whether programs exist, files and cassettes, resolution of scheduling variables and so on had to be eliminated in advance:

The customer uses the scheduling system “TWS for z/OS” (OPC) to run more than 65,000 z/OS jobs and 15,000 decentralized processes each day. HORIZONT SmartJCL was used to check the JCL. SmartJCL’s integrated simulation system made it possible to completely simulate the eleven production days required and to identify all possible errors in advance (“DATA SET NOT FOUND”, “REQUESTED MODULE NOT FOUND”, “UNDEFINED VARIABLE XYZ LINE 00008 OF ORIG JCL”)

A total of 453,406 jobs containing approx. 3 million steps were checked in approx. 6 hours.

The QA system had to be populated with the most current data possible – and of course with all the required data. To do this, the productive system of approx. 22 million files was mirrored in the QA system at a predetermined point in time. But the archived files and the files on cassette were still missing.

This is where the SmartJCL catalog check feature was able to help out. This SmartJCL feature simulates data flow across multiple jobs and reports data processing errors such as whether a file is missing or a file already exists. Optionally, this feature can also output a list of input files that are on cassette (specific VOLSER). The customer used this list to generate copy and recall jobs for integrating cassettes and their attached tape robots into the QA system.

SmartJCL checked the 450,000 jobs in the correct job run sequence and simulated the data processing of all 22 million files. Approx. 28,000 missing files were identified, primarily archived files on cassette.

With the help of Smart JCL, production planning came to the conclusion that nothing stood in the way of a complete test of the application package. SmartJCL had caught errors in advance, preventing additional costs.

Production planning has now started using the SmartJCL catalog check feature for other purposes, for example, checking an entire production month of approx. 870,000 jobs in advance.