/* 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); }