[hollowcelery]

There are a number of things that make code hard to reason about for humans, and combinatorial complexity is just one of them. Another one is, say, size of working memory, or having to navigate across a large number of files to understand a piece of logic. These two examples are not necessarily expensive for computers.

I don't entirely disagree that there is code that's objectively difficult to work with, but I suspect that the Venn diagram of "code that's hard for humans" and "code that's hard for computers" has much less overlap than you're suggesting.

[tombert]

Certainly with current models I have found that the Venn diagram of "code that's hard for humans" and "code that's hard for computers" has actually been remarkably similar, I suspect because it's trained on a lot of terrible code on Github.

I'm sure that these models will get better, and I agree that the overlap will be lower at that point, but I still think what I said will be true.

[bccdee]

I wouldn't expect so. These machines have been trained on natural language, after all. They see the world through an anthropomorphic lens. IME & from what I've heard, they struggle with inexpressive code in much the same way humans do.