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[yul-phaser] Tests for random number generators

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cameel 2020-01-24 03:32:56 +01:00
parent 24d63a93cf
commit ccaff1b08e
2 changed files with 96 additions and 0 deletions
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1
test/CMakeLists.txt
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@ -141,6 +141,7 @@ detect_stray_source_files("${libyul_sources}" "libyul/")
set(yul_phaser_sources
yulPhaser/Chromosome.cpp
yulPhaser/Program.cpp
yulPhaser/Random.cpp
# FIXME: yul-phaser is not a library so I can't just add it to target_link_libraries().
# My current workaround is just to include its source files here but this introduces

95
test/yulPhaser/Random.cpp Normal file
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@ -0,0 +1,95 @@
/*
This file is part of solidity.
solidity is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
solidity is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with solidity. If not, see <http://www.gnu.org/licenses/>.
*/
#include <tools/yulPhaser/Random.h>
#include <boost/test/unit_test.hpp>
#include <cassert>
using namespace std;
namespace solidity::phaser::test
{
BOOST_AUTO_TEST_SUITE(Phaser)
BOOST_AUTO_TEST_SUITE(RandomTest)
BOOST_AUTO_TEST_CASE(uniformRandomInt_returns_different_values_when_called_multiple_times)
{
constexpr uint32_t numSamples = 1000;
constexpr uint32_t numOutcomes = 100;
vector<uint32_t> samples1;
vector<uint32_t> samples2;
for (uint32_t i = 0; i < numSamples; ++i)
{
samples1.push_back(uniformRandomInt(0, numOutcomes - 1));
samples2.push_back(uniformRandomInt(0, numOutcomes - 1));
}
vector<uint32_t> counts1(numSamples, 0);
vector<uint32_t> counts2(numSamples, 0);
for (uint32_t i = 0; i < numSamples; ++i)
{
++counts1[samples1[i]];
++counts2[samples2[i]];
}
// This test rules out not only the possibility that the two sequences are the same but also
// that they're just different permutations of the same values. The test is probabilistic so
// it's technically possible for it to fail even if generator is good but the probability is
// so low that it would happen on average once very 10^125 billion years if you repeated it
// every second. The chance is much lower than 1 in 1000^100 / 100!.
//
// This does not really guarantee that the generated numbers have the right distribution or
// or that they don't come in long, repeating sequences but the implementation is very simple
// (it just calls a generator from boost) so our goal here is just to make sure it's used
// properly and we're not getting something totally non-random, e.g. the same number every time.
BOOST_TEST(counts1 != counts2);
}
BOOST_AUTO_TEST_CASE(binomialRandomInt_returns_different_values_when_called_multiple_times)
{
constexpr uint32_t numSamples = 1000;
constexpr uint32_t numTrials = 100;
constexpr double successProbability = 0.6;
vector<uint32_t> samples1;
vector<uint32_t> samples2;
for (uint32_t i = 0; i < numSamples; ++i)
{
samples1.push_back(binomialRandomInt(numTrials, successProbability));
samples2.push_back(binomialRandomInt(numTrials, successProbability));
}
vector<uint32_t> counts1(numSamples, 0);
vector<uint32_t> counts2(numSamples, 0);
for (uint32_t i = 0; i < numSamples; ++i)
{
++counts1[samples1[i]];
++counts2[samples2[i]];
}
// See remark for uniformRandomInt() above. Same applies here.
BOOST_TEST(counts1 != counts2);
}
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
}