Earlier quoted context omitted.
The nice thing about a vaguely English like language is that your average LLM is going to do a better job of making sense of it. Because it can leverage its learnings from the entire training set, not just the code-specific portion of it.
Not for generating it, because the more it looks like prose the more the LLM's output will be influenced by all the prose it's ingested.
It also does a reasonable job of generating working COBOL. I had to fix up just a few errors in the data definitions as the llm generated badly sized data members, but it was pretty smooth. Much smoother than my experiences with llm's and Python. What a crap shoot Python is with llm's...