At an insurance company, I encountered an application that had been in place for thirty years.
Classic flat-file, mainframe COBOL. And decades old.
It had never been replaced with a packaged solution. It had never been converted to a SQL database. It had never been rewritten in VB to run on a desktop.
What had happened is that it had grown and morphed organically. Pieces the original application it had been subsumed by other applications. Additional functionality had been grafted on.
After a few decades of staff turnover, no single person could summarize what the applications did. There was no executive overview. No pithy summary. No elevator pitch.
The company had, further, spent money to have consultants "reverse engineer" the COBOL. This meant that the consultants created narrative English-language versions of the COBOL code.
This reverse engineering replaced detailed, disorganized COBOL with detailed, disorganized English. No summaries were produced that could serve as an explanation of the actual valuable parts of the program.
The question of scope and duration was daunting. The conversion would take years to complete. the central question become "How to manage the conversion?"
The technical obstacle was the hellish complexity of the applications and their various shell scripts ("JCL" in the Z/OS mainframe world.)
One approach to overcoming the complexity is to break the overall collection of applications down into just those applications that write to any of the central "master" files. Other applications that read master files or do other processing are less important than those which update the master files.
The master files themselves are easy to identify. The JCL that references these files is easy to identify.
The programs run by those JCL scripts give us clusters of related functionality.
We want to rank the master files by business value. The one with the most valuable data is something we tackle first. The least valuable data we leave for last.
In some cases, we'll identify programs that work with relatively low-value data; programs which are not actually assets. They don't encode any new, useful knowledge. A wise manager can elect to remove them from the software inventory rather than convert them.
Since the conversion can't happen overnight, there needs to be a period of coexistence between the first conversion and the last. And this coexistence means that database tables will get extracted back to flat files so that legacy programs can continue to operate.
Another component of the plan for this conversion was the assembly of test cases. This is critical when refactoring code.
The idea here is to preserve selected files and run them through the application software to create repeatable test cases. One of the existing file-compare utilities can be used to validate the output.
Experienced mainframe people could not see how a "little" Linux processor could ever provide the amazing feature set and performance of their beloved mainframe. They made the case that CICS was higher performance and more scalable than any web-based application platform.
And that lead to an impasse where one camp refused to consider any migration except to COBOL and CICS. The other camp simply wanted to write a web application and be done with it.
The COBOL/CICS group were either confused on in denial of how quick and simple to can be to build default web applications around stable data models. In this case, the relational database version of the flat files would not be difficult to concoct. Once built, 80% of the application programming would be default add-change-delete transactions. The other 20% would be transactions that included the remnants of useful knowledge encoded in the legacy COBOL.
More time would be spent "studying the alternatives" than were required to build working prototypes.
Clearly, the data is central to the business.
The larger question, then, is how much of the COBOL processing was really essential processing?
How much of the COBOL was technical workaround to implement things that are one-liners in SQL?
How much of the COBOL is workaround for other bugs in other applications? How many programs fix broken interface files? How many programs provide data quality inspections?
How much of the COBOL is actually unique? A substantial fraction of the legacy code was irrelevant because a package replaced it. Another substantial fraction implemented a "Customer Relationship Management" (CRM) application for which a package might have been a better choice than a software conversion.
How much of the legacy code contain quirks? How much code would we would have to understand and consider repairing because it actually contains a long-standing bug?
Perhaps the only thing of value was the data.
And perhaps the reason for the human obstacle was an realization that the cost to convert exceeded the value being preserved. It's difficult to have your life's work simply discarded.
Classic flat-file, mainframe COBOL. And decades old.
It had never been replaced with a packaged solution. It had never been converted to a SQL database. It had never been rewritten in VB to run on a desktop.
What had happened is that it had grown and morphed organically. Pieces the original application it had been subsumed by other applications. Additional functionality had been grafted on.
After a few decades of staff turnover, no single person could summarize what the applications did. There was no executive overview. No pithy summary. No elevator pitch.
The company had, further, spent money to have consultants "reverse engineer" the COBOL. This meant that the consultants created narrative English-language versions of the COBOL code.
This reverse engineering replaced detailed, disorganized COBOL with detailed, disorganized English. No summaries were produced that could serve as an explanation of the actual valuable parts of the program.
The question of scope and duration was daunting. The conversion would take years to complete. the central question become "How to manage the conversion?"
The Goal
The goal was to preserve the valuable features while migrating the data out of flat files into a proper SQL database. The focus on the data was important.The technical obstacle was the hellish complexity of the applications and their various shell scripts ("JCL" in the Z/OS mainframe world.)
One approach to overcoming the complexity is to break the overall collection of applications down into just those applications that write to any of the central "master" files. Other applications that read master files or do other processing are less important than those which update the master files.
The master files themselves are easy to identify. The JCL that references these files is easy to identify.
The programs run by those JCL scripts give us clusters of related functionality.
We want to rank the master files by business value. The one with the most valuable data is something we tackle first. The least valuable data we leave for last.
In some cases, we'll identify programs that work with relatively low-value data; programs which are not actually assets. They don't encode any new, useful knowledge. A wise manager can elect to remove them from the software inventory rather than convert them.
Since the conversion can't happen overnight, there needs to be a period of coexistence between the first conversion and the last. And this coexistence means that database tables will get extracted back to flat files so that legacy programs can continue to operate.
Another component of the plan for this conversion was the assembly of test cases. This is critical when refactoring code.
The idea here is to preserve selected files and run them through the application software to create repeatable test cases. One of the existing file-compare utilities can be used to validate the output.
Other Barriers
The human obstacle was triumphant here. People who had worked with this software for their entire career in IT would rather quit than help with the conversion.Experienced mainframe people could not see how a "little" Linux processor could ever provide the amazing feature set and performance of their beloved mainframe. They made the case that CICS was higher performance and more scalable than any web-based application platform.
And that lead to an impasse where one camp refused to consider any migration except to COBOL and CICS. The other camp simply wanted to write a web application and be done with it.
The COBOL/CICS group were either confused on in denial of how quick and simple to can be to build default web applications around stable data models. In this case, the relational database version of the flat files would not be difficult to concoct. Once built, 80% of the application programming would be default add-change-delete transactions. The other 20% would be transactions that included the remnants of useful knowledge encoded in the legacy COBOL.
More time would be spent "studying the alternatives" than were required to build working prototypes.
Preservation
The real question is one of what needs to be preserved.Clearly, the data is central to the business.
The larger question, then, is how much of the COBOL processing was really essential processing?
How much of the COBOL was technical workaround to implement things that are one-liners in SQL?
How much of the COBOL is workaround for other bugs in other applications? How many programs fix broken interface files? How many programs provide data quality inspections?
How much of the COBOL is actually unique? A substantial fraction of the legacy code was irrelevant because a package replaced it. Another substantial fraction implemented a "Customer Relationship Management" (CRM) application for which a package might have been a better choice than a software conversion.
How much of the legacy code contain quirks? How much code would we would have to understand and consider repairing because it actually contains a long-standing bug?
Perhaps the only thing of value was the data.
And perhaps the reason for the human obstacle was an realization that the cost to convert exceeded the value being preserved. It's difficult to have your life's work simply discarded.
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