This is an incredibly out of date course. It should have been offered in 2014, not 2024. They barely talk about any paper published after 2005 or so. The latest paper is a survey from 2019.
I think, maybe, the stronger argument is that the area of Generative Programming (which covers just about anything that generates another program) itself is too broad to properly address in a semester course. This course is particularly focused on metaprogramming, where ML has less relevance. This is to be expected, given the instructor.
It's fairly common practice for the title of the course to be far more broad than the topic. See: "Theory of Computing" courses which spend all their time on complexity classes and never mention automata, or graph theory courses which don't ever mention monadic second order logic or spectral graph theory. Decisions have to be made about what to keep and what to cut, at some point.
I spend a lot of time reading papers at the intersection of ML & PL, so I'm a bit sad, personally, but I don't think it's fair to say the course is out of date. Rather, this is just a sign of the known world getting bigger.
Yeah, I would hard disagree. It's a disservice to students to teach this course as is.
Students need to get up to date on a topic so that they can do research if they want. Teaching a course that's 10-20 years out of date is a serious problem. They won't know what questions people ask now, they won't know any of the current players, etc.
This isn't a generic ToC course. This is supposed to be a survey of research. Nowhere does it make it clear that this is vastly outdated research.
> I spend a lot of time reading papers at the intersection of ML & PL, so I'm a bit sad, personally, but I don't think it's fair to say the course is out of date. Rather, this is just a sign of the known world getting bigger.
Or maybe.. I've taught survey courses of ML/PL and I'm very familiar with the subject matter and was shocked to not see any relevant research on that page?
I guess generative AI using copilot or ChatGPT might overtake model-driven engineering as a time-saving technique, which seems worrisome for the "software factory" industry. At the same time, I doubt it will replace MDE as a formal method (i.e. if you need to prove that your software does what it is supposed to do).
It misses all of machine learning as a whole.