| /* |
| * 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" |
| |
| 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"; |
| } |