Concordion is an open source tool for writing
automated acceptance tests in Java*
* There are also versions for .NET, Python, and Ruby. [More details]
“Lets you write business tests that don't assume a particular implementation.”
Key Features
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Powerful, yet simple to use Concordion integrates directly with JUnit.
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Highly readable tests Concordion acceptance tests are so readable they can double up as system documentation. And, since the tests are linked to the system, you know the documentation is always up-to-date.
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Separates tests from implementation Tests that include a lot of implementation detail lock you into that implementation. Concordion helps you to document the logic and behaviour of your system in a way that does not
The Fresnel Vocabulary for RDF provides a way to write down a set of instructions for transforming RDF statements into HTML for display. For some time, the ORDF library has included two implementations of Fresnel, one in JavaScript and one in Python. Recently added is a command line tool, simply called fresnel, for rendering HTML documents given a lens and an RDF graph.
Music21 is a set of tools for helping scholars and other active listeners answer questions about music quickly and simply. If you’ve ever asked yourself a question like, “I wonder how often Bach does that” or “I wish I knew which band was the first to use these chords in this order,” or “I’ll bet we’d know more about Renaissance counterpoint (or Indian ragas or post-tonal pitch structures or the form of minuets) if I could write a program to automatically write more of them,” then music21 can help you with your work.
PyBrain is a modular Machine Learning Library for Python. Its goal is to offer flexible, easy-to-use yet still powerful algorithms for Machine Learning Tasks and a variety of predefined environments to test and compare your algorithms.
PyBrain is short for Python-Based Reinforcement Learning, Artificial Intelligence and Neural Network Library.
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R. Okuta, Y. Unno, D. Nishino, S. Hido, and C. Loomis. Proceedings of Workshop on Machine Learning Systems (LearningSys) in The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS), (2017)
K. Rivers, E. Harpstead, and K. Koedinger. Proceedings of the 2016 ACM Conference on International Computing Education Research, page 143--151. New York, NY, USA, ACM, (2016)