mcmc-synthesis: MCMC applied to probabilistic program synthesis
A simple implementation of the ideas from "Stochastic Superoptimization" which uses a variant of Markov Chain Monte Carlo (MCMC) to synthesize programs based on a set of test cases. "Stochastic Superoptimization": http://cs.stanford.edu/people/eschkufz/research/asplos291-schkufza.pdf
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- mcmc-synthesis-0.1.2.2.tar.gz [browse] (Cabal source package)
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| Versions [RSS] | 0.1.0.4, 0.1.0.5, 0.1.1.0, 0.1.1.1, 0.1.2.1, 0.1.2.2 |
|---|---|
| Dependencies | base (>3 && <=5), MonadRandom (>=0.1 && <0.2) [details] |
| License | GPL-3.0-only |
| Author | Jessica Taylor <jessica.liu.taylor@gmail.com>, Tikhon Jelvis <tikhon@jelv.is> |
| Maintainer | Jessica Taylor <jessica.liu.taylor@gmail.com> |
| Category | Language |
| Source repo | head: git clone git://github.com/jacobt/mcmc-synthesis.git |
| Uploaded | by TikhonJelvis at 2014-04-13T00:44:24Z |
| Distributions | |
| Reverse Dependencies | 2 direct, 1 indirect [details] |
| Downloads | 4365 total (6 in the last 30 days) |
| Rating | (no votes yet) [estimated by Bayesian average] |
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| Status | Docs available [build log] Successful builds reported [all 1 reports] |