Watsonx: IBM's code assistant for turning COBOL into Java

The article title is clickbaity, but the actual point is the proposal of using LLMs to translate large amounts of legacy COBOL systems to more modern languages like Java. Doesn't seem terribly useful to me. I expect you could get a 90% solution faster, but the whole challenge with these projects is how to get that last bit of correctness, and how to be confident enough in the correctness of it to actually use it in Production.

But then all of this has been known for decades. There are plenty of well-known techniques for how to do all that. If they haven't actually done it by now, it's a management problem, and no AI tech is going to fix that.

How hard is it to actually learn COBOL? It seems like a fairly simple language to pick up, but maybe the idiomatic COBOL used in these legacy systems is particularly nasty for some reason.

COBOL is pretty easy to learn. The problem is that it is so full of archaic nonsense (less so with the more recent versions) that you will be tearing your hair out and wishing for something more modern.

COBOL's main value is in maintaining a pile of legacy codebases, mostly in fintech and insurance that are so large and so old that rewriting them is an absolute no-go. These attempts at cross compiling are a way to get off the old toolchain but they - in my opinion - don't really solve the problem, instead they add another layer of indirection (code generation). But at least you'll be able to run your mangled output on the JVM for whatever advantage that gives you.

With some luck you'll be running a hypervisor that manages a bunch of containers that run multiple JVM instances each that run Java that was generated from some COBOL spaghetti that nobody fully understands. If that stops working I hope I will be far, far away from the team that has to figure out what causes the issue.

It is possible that someone somewhere is doing greenfield COBOL development but I would seriously question their motivations.

> that rewriting them is an absolute no-go

Rewriting and expecting 100% feature-parity (and bug-parity, since any bugs/inconsistencies are most likely relied upon by now) is realistically impossible.

However, new banking/insurance startups proved you can build this stuff from scratch using modern tooling, so the migration path would be to create your own "competitor" and then move your customers onto it.

The problem I see is that companies that still run these legacy systems also have a legacy culture fundamentally incompatible with what's needed to build and retain a competent engineering team. Hell, there's probably also a lot of deadweight whose jobs are to make up for the shortcomings of the legacy system and who'd have every incentive to sabotage the migration/rebuild project.

That happens, but what also happens is that everybody is painfully aware of the situation and they do the best they can. Just like you or I would.

And of course, if you start a bank today you'd do the whole cycle all over again, shiny new tech, that in a decade or two is legacy that nobody dares to touch. Because stuff like this is usually industry wide: risk adversity translates into tech debt in the long term.

I suspect that the only thing that will cure this is for technology to stop being such a moving target. Once we reach that level we can maybe finally call it engineering, accept some responsibility (and liability) and professionalize. Until then this is how it will be.

Why would software technology ever stop moving? To a first approximation it is unconstrained by physical reality (unlike other engineering disciplines) so I expect it will keep moving at roughly the same rate. Maybe even accelerate in some areas.

Individual organizations can consciously choose to slow down. Which works for a while in terms of boosting quality and productivity. But over the long run they inevitably fall behind and an upstart competitor with a new business model enabled by new software technology eventually eats their lunch.

Software technology moves when we figure out new ways of doing software that bring some kind of advantage. If no one is finding new ways to do software that have any purpose, technology will stop moving. Physical reality doesn't really have anything to do with it - we're limited by human ingenuity, and possibly by the mathematical space of algorithms (though that's likely to be much larger).

For an example of this happening in a field, look at the glacial pace of advancement in theoretical physics for the last few decades, compared to 1900s. Or at the pace of development in physics in general in the centuries before.