/*
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 .
*/
#include
// NOTE: The code would work with std::random but the results for a given seed would not be reproducible
// across different STL implementations. Boost does not guarantee this either but at least it has only one
// implementation. Reproducibility is not a hard requirement for yul-phaser but it's nice to have.
#include
#include
#include
#include
#include
using namespace std;
using namespace solidity;
using namespace solidity::phaser;
thread_local boost::random::mt19937 SimulationRNG::s_generator(SimulationRNG::generateSeed());
bool SimulationRNG::bernoulliTrial(double _successProbability)
{
boost::random::bernoulli_distribution distribution(_successProbability);
return distribution(s_generator);
}
size_t SimulationRNG::uniformInt(size_t _min, size_t _max)
{
boost::random::uniform_int_distribution distribution(_min, _max);
return distribution(s_generator);
}
size_t SimulationRNG::binomialInt(size_t _numTrials, double _successProbability)
{
// NOTE: binomial_distribution would not work because it internally tries to use abs()
// and fails to compile due to ambiguous conversion.
assert(_numTrials <= static_cast(numeric_limits::max()));
boost::random::binomial_distribution distribution(static_cast(_numTrials), _successProbability);
return static_cast(distribution(s_generator));
}
uint32_t SimulationRNG::generateSeed()
{
// This is not a secure way to seed the generator but it's good enough for simulation purposes.
// The only thing that matters for us is that the sequence is different on each run and that
// it fits the expected distribution. It does not have to be 100% unpredictable.
return time(nullptr);
}