1 | /* |
2 | * Copyright (c) 2016, Oracle and/or its affiliates. All rights reserved. |
3 | * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. |
4 | * |
5 | * This code is free software; you can redistribute it and/or modify it |
6 | * under the terms of the GNU General Public License version 2 only, as |
7 | * published by the Free Software Foundation. |
8 | * |
9 | * This code is distributed in the hope that it will be useful, but WITHOUT |
10 | * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
11 | * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
12 | * version 2 for more details (a copy is included in the LICENSE file that |
13 | * accompanied this code). |
14 | * |
15 | * You should have received a copy of the GNU General Public License version |
16 | * 2 along with this work; if not, write to the Free Software Foundation, |
17 | * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. |
18 | * |
19 | * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA |
20 | * or visit www.oracle.com if you need additional information or have any |
21 | * questions. |
22 | * |
23 | */ |
24 | |
25 | #include "precompiled.hpp" |
26 | #include "gc/g1/g1Predictions.hpp" |
27 | #include "unittest.hpp" |
28 | |
29 | static const double epsilon = 1e-6; |
30 | |
31 | // Some basic formula tests with confidence = 0.0 |
32 | TEST_VM(G1Predictions, basic_predictions) { |
33 | G1Predictions predictor(0.0); |
34 | TruncatedSeq s; |
35 | |
36 | double p0 = predictor.get_new_prediction(&s); |
37 | ASSERT_LT(p0, epsilon) << "Initial prediction of empty sequence must be 0.0" ; |
38 | |
39 | s.add(5.0); |
40 | double p1 = predictor.get_new_prediction(&s); |
41 | ASSERT_NEAR(p1, 5.0, epsilon); |
42 | |
43 | for (int i = 0; i < 40; i++) { |
44 | s.add(5.0); |
45 | } |
46 | double p2 = predictor.get_new_prediction(&s); |
47 | ASSERT_NEAR(p2, 5.0, epsilon); |
48 | } |
49 | |
50 | // The following tests checks that the initial predictions are based on |
51 | // the average of the sequence and not on the stddev (which is 0). |
52 | TEST_VM(G1Predictions, average_not_stdev_predictions) { |
53 | G1Predictions predictor(0.5); |
54 | TruncatedSeq s; |
55 | |
56 | s.add(1.0); |
57 | double p1 = predictor.get_new_prediction(&s); |
58 | ASSERT_GT(p1, s.davg()) << "First prediction must be greater than average" ; |
59 | |
60 | s.add(1.0); |
61 | double p2 = predictor.get_new_prediction(&s); |
62 | ASSERT_GT(p1, p2) << "First prediction must be greater than second" ; |
63 | |
64 | s.add(1.0); |
65 | double p3 = predictor.get_new_prediction(&s); |
66 | ASSERT_GT(p2, p3) << "Second prediction must be greater than third" ; |
67 | |
68 | s.add(1.0); |
69 | s.add(1.0); // Five elements are now in the sequence. |
70 | double p4 = predictor.get_new_prediction(&s); |
71 | ASSERT_LT(p4, p3) << "Fourth prediction must be smaller than third" ; |
72 | ASSERT_NEAR(p4, 1.0, epsilon); |
73 | } |
74 | |
75 | // The following tests checks that initially prediction based on |
76 | // the average is used, that gets overridden by the stddev prediction at |
77 | // the end. |
78 | TEST_VM(G1Predictions, average_stdev_predictions) { |
79 | G1Predictions predictor(0.5); |
80 | TruncatedSeq s; |
81 | |
82 | s.add(0.5); |
83 | double p1 = predictor.get_new_prediction(&s); |
84 | ASSERT_GT(p1, s.davg()) << "First prediction must be greater than average" ; |
85 | |
86 | s.add(0.2); |
87 | double p2 = predictor.get_new_prediction(&s); |
88 | ASSERT_GT(p1, p2) << "First prediction must be greater than second" ; |
89 | |
90 | s.add(0.5); |
91 | double p3 = predictor.get_new_prediction(&s); |
92 | ASSERT_GT(p2, p3) << "Second prediction must be greater than third" ; |
93 | |
94 | s.add(0.2); |
95 | s.add(2.0); |
96 | double p4 = predictor.get_new_prediction(&s); |
97 | ASSERT_GT(p4, p3) << "Fourth prediction must be greater than third" ; |
98 | } |
99 | |