I get asked every so often to release the source code for my random art project. The original source is written in Ocaml and is not publicly available, but here is a simple example of how you can get random art going in python in 250 lines of code.
Download source: randomart.py
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These are the slides and the extended abstract from my MSFP 2008 talk. Apparently, I forgot to publish them online. There is a discussion on the Agda mailing list to which the talk is somewhat relevant, so I am publishing now.
Abstract: Realizability is an interpretation of intuitionistic logic which subsumes the Curry-Howard interpretation of propositions as types, because it allows the realizers to use computational effects such as non-termination, store and exceptions. Therefore, we can use realizability as a framework for program development and extraction which allows any style of programming, not just the purely functional one that is supported by the Curry-Howard correspondence. In joint work with Christopher A. Stone we developed RZ, a tool which uses realizability to translate specifications written in constructive logic into interface code annotated with logical assertions. RZ does not extract code from proofs, but allows any implementation method, from handwritten code to code extracted from proofs by other tools. In our experience, RZ is useful for specification of non-trivial theories. While the use of computational effects does improve efficiency it also makes it difficult to reason about programs and prove their correctness. We demonstrate this fact by considering non-purely functional realizers for a Brouwerian continuity principle.
Download: msfp2008-slides.pdf, msfp2008-abstract.pdf
I have aded to the PL Zoo a mini prolog interpreter. It really is minimalistic, as it only handles pure Horn clauses. There is no arithmetic, lists, cuts, or disjunctions. Nevertheless, it ought to be possible to write a miniml interpreter in it… If anyone does it, please send me the code!
I have added two new languages to the PL Zoo. The minor addition is miniml+error, which is just MiniML with an error exception (raised by division by 0) that cannot be caught. The purpose is to demonstrate handling of fatal errors during runtime. The more interesting new animal is levy (written by Matija Pretnar and myself), an implementation of Paul Levy’s call-by-push-value language. If you only know about Haskell’s call-by-name and ML’s call-by-value, I invite you to learn about call-by-push-value. Start by reading Paul’s FAQ.
Back in 2000 John Langford of the Machine Learning (Theory) blog and I wrote a backup script which I am still using today. A number of other people have found it useful so I decided to release it under an open source license. The script is easy to use under Linux. I am told it also backs up Windows with a bit of tweaking.
Continue reading Remote Backup with Secure Shell and Rsync