I've worked at many financial institutions and government agencies, and they all have extremely old mainframe systems running COBOL. Every time the executives bolster "We're finally going to move off of this old system and modernize", I show them the price and they scamper off into their back rooms to whine about profit margins. It's always fun when something does go wrong with those systems and they go through the cycle all over again, but now it's even more expensive to fix
IBM, eager to keep those legacy functions on its Z mainframe systems, wants that code rewritten in Java.
In a technical blog post specific to COBOL conversion, IBM's Kyle Charlet, CTO for zSystems software, steps up to the plate and says what a lot of people have said about COBOL: It's not just the code; it's the business logic, the edge-cases, and the institutional memory, or the lack thereof.
IBM's watsonx, Charlet writes, could help large organizations decouple individual services from monolithic COBOL apps.
While COBOL codebases can be relatively stable and secure—once found to be among the least problematic in a broad survey—the costs of updating and extending them are gigantic.
Legacy COBOL was one of the reasons the Office of Personnel Management suffered a deeply intrusive break-in in 2015, as the antiquated code could not be encrypted or made to work with other secure systems.
But there's a recurring argument that COBOL is good at managing business-specific systems and exchanges in ways that (some might argue) present fewer attack vectors.
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tbh refactoring (if it can be done safely) could be a huge help to orgs and fantastic AI use case. Rarely do businesses want to spend the resources to improve a codebase. Hope it goes well for IBM.
How can you verify that it's actually running safely? If you'd have a comprehensive testing framework in place, you wouldn't need AI driven refactoring in the first place.
You could code review the commits it makes I suppose. Saves you having to think of how to refactor something but still makes it fairly easy to mitigate the AI doing something terribly wrong.