| 209 | } |
| 210 | |
| 211 | static void ApproximateBestSubset(const std::vector<OutputGroup>& groups, const CAmount& nTotalLower, const CAmount& nTargetValue, |
| 212 | std::vector<char>& vfBest, CAmount& nBest, int iterations = 1000) |
| 213 | { |
| 214 | std::vector<char> vfIncluded; |
| 215 | |
| 216 | vfBest.assign(groups.size(), true); |
| 217 | nBest = nTotalLower; |
| 218 | |
| 219 | FastRandomContext insecure_rand; |
| 220 | |
| 221 | for (int nRep = 0; nRep < iterations && nBest != nTargetValue; nRep++) |
| 222 | { |
| 223 | vfIncluded.assign(groups.size(), false); |
| 224 | CAmount nTotal = 0; |
| 225 | bool fReachedTarget = false; |
| 226 | for (int nPass = 0; nPass < 2 && !fReachedTarget; nPass++) |
| 227 | { |
| 228 | for (unsigned int i = 0; i < groups.size(); i++) |
| 229 | { |
| 230 | //The solver here uses a randomized algorithm, |
| 231 | //the randomness serves no real security purpose but is just |
| 232 | //needed to prevent degenerate behavior and it is important |
| 233 | //that the rng is fast. We do not use a constant random sequence, |
| 234 | //because there may be some privacy improvement by making |
| 235 | //the selection random. |
| 236 | if (nPass == 0 ? insecure_rand.randbool() : !vfIncluded[i]) |
| 237 | { |
| 238 | nTotal += groups[i].GetSelectionAmount(); |
| 239 | vfIncluded[i] = true; |
| 240 | if (nTotal >= nTargetValue) |
| 241 | { |
| 242 | fReachedTarget = true; |
| 243 | if (nTotal < nBest) |
| 244 | { |
| 245 | nBest = nTotal; |
| 246 | vfBest = vfIncluded; |
| 247 | } |
| 248 | nTotal -= groups[i].GetSelectionAmount(); |
| 249 | vfIncluded[i] = false; |
| 250 | } |
| 251 | } |
| 252 | } |
| 253 | } |
| 254 | } |
| 255 | } |
| 256 | |
| 257 | // ELEMENTS: |
| 258 | std::optional<SelectionResult> KnapsackSolver(std::vector<OutputGroup>& groups, const CAmountMap& mapTargetValue) |
no test coverage detected