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README

Introduction
------------

CxxTest is a JUnit/CppUnit/xUnit-like framework for C++.

Its advantages over existing alternatives are that it:
- Doesn't require RTTI
- Doesn't require member template functions
- Doesn't require exception handling
- Doesn't require any external libraries (including memory management,
file/console I/O, graphics libraries)

This makes it extremely portable and usable.

CxxTest is available under the GNU Lesser General Public Licence (LGPL).
See http://www.gnu.org/copyleft/lesser.html for the license.

Simple user's guide
-------------------

1. Create a test suite header file:

MyTest.h:
#include

class MyTestSuite : public CxxTest::TestSuite
{
public:
void testAddition( void )
{
TS_ASSERT( 1 + 1 > 1 );
TS_ASSERT_EQUALS( 1 + 1, 2 );
}
};


2. Generate the tests file:

# cxxtestgen.pl -o tests.cpp MyTestSuite.h


3. Create a main function that runs the tests

main.cpp:
#include

int main( void )
{
CxxText::ErrorPrinter::runAllTests();
return 0;
}


4. Compile and run!

# g++ -o main main.cpp tests.cpp
# ./main
Running 1 test(s).OK!


Advanced User's Guide
---------------------
See docs/guide.html.
datacite.yml
Title ObjSim
Authors Michler,Frank;Philipps-Universität Marburg
Philipp,Sebastian Thomas
Description C++ library for simulating spiking neural networks.
License X11 License (https://spdx.org/licenses/X11.html)
References Michler F, Eckhorn R, Wachtler T (2009): Using Spatiotemporal Correlations to Learn Topographic Maps for Invariant Object Recognition. J Neurophysiol 102:953-64. [doi:10.1152/jn.90651.2008] (IsSupplementTo)
Michler F, Wachtler T, Eckhorn R (2006): Adaptive Feedback Inhibition Improves Pattern Discrimination Learning. Lecture Notes in Artificial Intelligence 4087:21-32. [doi:10.1007/11829898_3] (IsSupplementTo)
Funding DFG, EC 53/11
DFG, DFG.5471310
Keywords Neuroscience
Spiking Neural Networks
Topographic Maps
Object Recognition
Resource Type Software