Nice to see this do so well over here. I posted this to /r/Racket earlier and as I said over there:
> This has screencasts or at least slides for most lectures. I have just started going through it myself and plan to "audit" all the lectures and do the homework assignments. Anyone have an interest in this and would like a virtual study buddy?
It's also worth pointing out that this excellent RacketCon talk [1] made me go seek out more about Excel Flash Fill [2] and in seeking to understand how that works I stumbled upon this course.
Thanks for linking that! I hadn't seen it and I _had_ been searching YouTube for lectures on FlashFill but the popularity of this feature made it hard to find anything other than tutorials on using it in Excel.
Oh hey, I actually took this class. Funny to see it linked on HN. It was easily the single most valuable class I took in undergrad.
There's definitely a lot of useful information there, but I'm not sure how well it's organized because the course website wasn't designed to stand on its own.
It's about making tools that help with the structural aspects of generating code. It's not part of machine learning, but rather it's very much about symbolic/analytic/logical production of code based on a specification of some sort.
I mean just about every thing was AI at one point; program synthesis was seen as AI (like in the 70s) right up until it wasn't after we effectively encoded it into programming languages. For example lisp it self was effectively AI research as well. In computer science it's pretty typical to refer to things as AI right up until we understand how to engineer it; the history of email that was posted recently is a great example (at first we just had computers extracting features and learning things, and it was vague and generic; these days we understand the system as a reputation network, and we understand the details of each of the features because it required a bunch of engineering to make that specific solution scale and fast).
A lot of the recent work here takes advantage of SMT solvers (next generation of SAT solvers), but that's not necessary. As with Viv and Flash Fill, a lot of it is about changing the concept of what it means to write a program, and use alternative approaches to "complete" it. As another example, generating 0-day bug fixes based on how code "should" look, or recommending typed completions to gaps in code.
For my past work in that group, I looked at "sketching" efficient schedules for parallel code, where I only specified the bits I cared about. Nowadays, I think about automatically generating queries for visual analytics.
I think the clearest example of an application that comes from these techniques is Excel Flash Fill and this course goes over the algorithm used in the Flash Fill paper.
I'm not sure what you mean by this question. What that lecture covers is essentially how to express an approximation of the operational semantics of a simple language as a logic formula in a very specific kind of logic (ie one of the theories supported by the Z3 SMT solver). It only supports a small number of constructs and data types, and handles infinite loops by placing an arbitrary bound on how far a program can run. It doesn't tell you anything about "all programs" or "all functions".
> This has screencasts or at least slides for most lectures. I have just started going through it myself and plan to "audit" all the lectures and do the homework assignments. Anyone have an interest in this and would like a virtual study buddy?
It's also worth pointing out that this excellent RacketCon talk [1] made me go seek out more about Excel Flash Fill [2] and in seeking to understand how that works I stumbled upon this course.
[1]: https://www.youtube.com/watch?v=nOyIKCszNeI&list=PLXr4KViVC0...
[2]: http://research.microsoft.com/en-us/um/people/sumitg/flashfi...