/* * Copyright (c) 2016, Oracle and/or its affiliates. All rights reserved. * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. * * This code is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 2 only, as * published by the Free Software Foundation. * * This code 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 * version 2 for more details (a copy is included in the LICENSE file that * accompanied this code). * * You should have received a copy of the GNU General Public License version * 2 along with this work; if not, write to the Free Software Foundation, * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. * * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA * or visit www.oracle.com if you need additional information or have any * questions. * */ #include "precompiled.hpp" #include "gc/g1/g1Predictions.hpp" #include "unittest.hpp" #include "utilities/ostream.hpp" static const double epsilon = 1e-6; // Some basic formula tests with confidence = 0.0 TEST_VM(G1Predictions, basic_predictions) { G1Predictions predictor(0.0); TruncatedSeq s; double p0 = predictor.get_new_prediction(&s); ASSERT_LT(p0, epsilon) << "Initial prediction of empty sequence must be 0.0"; s.add(5.0); double p1 = predictor.get_new_prediction(&s); ASSERT_NEAR(p1, 5.0, epsilon); for (int i = 0; i < 40; i++) { s.add(5.0); } double p2 = predictor.get_new_prediction(&s); ASSERT_NEAR(p2, 5.0, epsilon); } // The following tests checks that the initial predictions are based on // the average of the sequence and not on the stddev (which is 0). TEST_VM(G1Predictions, average_not_stdev_predictions) { G1Predictions predictor(0.5); TruncatedSeq s; s.add(1.0); double p1 = predictor.get_new_prediction(&s); ASSERT_GT(p1, s.davg()) << "First prediction must be greater than average"; s.add(1.0); double p2 = predictor.get_new_prediction(&s); ASSERT_GT(p1, p2) << "First prediction must be greater than second"; s.add(1.0); double p3 = predictor.get_new_prediction(&s); ASSERT_GT(p2, p3) << "Second prediction must be greater than third"; s.add(1.0); s.add(1.0); // Five elements are now in the sequence. double p4 = predictor.get_new_prediction(&s); ASSERT_LT(p4, p3) << "Fourth prediction must be smaller than third"; ASSERT_NEAR(p4, 1.0, epsilon); } // The following tests checks that initially prediction based on // the average is used, that gets overridden by the stddev prediction at // the end. TEST_VM(G1Predictions, average_stdev_predictions) { G1Predictions predictor(0.5); TruncatedSeq s; s.add(0.5); double p1 = predictor.get_new_prediction(&s); ASSERT_GT(p1, s.davg()) << "First prediction must be greater than average"; s.add(0.2); double p2 = predictor.get_new_prediction(&s); ASSERT_GT(p1, p2) << "First prediction must be greater than second"; s.add(0.5); double p3 = predictor.get_new_prediction(&s); ASSERT_GT(p2, p3) << "Second prediction must be greater than third"; s.add(0.2); s.add(2.0); double p4 = predictor.get_new_prediction(&s); ASSERT_GT(p4, p3) << "Fourth prediction must be greater than third"; } // Some tests to verify bounding between [0 .. 1] TEST_VM(G1Predictions, unit_predictions) { G1Predictions predictor(0.5); TruncatedSeq s; double p0 = predictor.get_new_unit_prediction(&s); ASSERT_LT(p0, epsilon) << "Initial prediction of empty sequence must be 0.0"; s.add(100.0); double p1 = predictor.get_new_unit_prediction(&s); ASSERT_NEAR(p1, 1.0, epsilon); // Feed the sequence additional positive values to test the high bound. for (int i = 0; i < 3; i++) { s.add(2.0); } ASSERT_NEAR(predictor.get_new_unit_prediction(&s), 1.0, epsilon); // Feed the sequence additional large negative value to test the low bound. for (int i = 0; i < 4; i++) { s.add(-200.0); } ASSERT_NEAR(predictor.get_new_unit_prediction(&s), 0.0, epsilon); } // Some tests to verify bounding between [0 .. +inf] TEST_VM(G1Predictions, lower_bound_zero_predictions) { G1Predictions predictor(0.5); TruncatedSeq s; double p0 = predictor.get_new_lower_zero_bound_prediction(&s); ASSERT_LT(p0, epsilon) << "Initial prediction of empty sequence must be 0.0"; s.add(100.0); // Feed the sequence additional positive values to see that the high bound is not // bounded by e.g. 1.0 for (int i = 0; i < 3; i++) { s.add(2.0); } ASSERT_GT(predictor.get_new_lower_zero_bound_prediction(&s), 1.0); // Feed the sequence additional large negative value to test the low bound. for (int i = 0; i < 4; i++) { s.add(-200.0); } ASSERT_NEAR(predictor.get_new_lower_zero_bound_prediction(&s), 0.0, epsilon); }