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Moves summary tests to the separate module and fix bug with empty summary generation for the Stats.of (#239)
* Added the initial solution for the bug fix * Disabled tests * Disabled integration tests * Removed comments * Added comments and renamed methods * Renamed method * Fixed test after the method renaming * Fixed the regular expression
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14 files changed

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‎settings.gradle

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@@ -16,4 +16,5 @@ include 'utbot-instrumentation-tests'
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include 'utbot-summary'
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include 'utbot-gradle'
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include 'utbot-maven'
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include 'utbot-summary-tests'
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‎utbot-analytics/build.gradle

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@@ -5,7 +5,6 @@ configurations {
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mlmodels
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}
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8-
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def osName = System.getProperty('os.name').toLowerCase().split()[0]
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if (osName == "mac") osName = "macosx"
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String classifier = osName + "-x86_64"
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}
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test {
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useJUnitPlatform {
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excludeTags 'Summary'
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}
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}
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processResources {

‎utbot-sample/src/main/java/guava/examples/math/Stats.java

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/*
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* Copyright (C) 2012 The Guava Authors
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*
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* Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
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* in compliance with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software distributed under the License
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* is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
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* or implied. See the License for the specific language governing permissions and limitations under
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* the License.
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*/
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package guava.examples.math;
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import java.io.Serializable;
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import java.util.Iterator;
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public final class Stats implements Serializable {
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private final long count;
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private final double mean;
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private final double sumOfSquaresOfDeltas;
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private final double min;
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private final double max;
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/**
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* Internal constructor. Users should use {@link #ofIterable} or {@link StatsAccumulator#snapshot}.
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*
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* <p>To ensure that the created instance obeys its contract, the parameters should satisfy the
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* following constraints. This is the callers responsibility and is not enforced here.
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*
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* <ul>
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* <li>If {@code count} is 0, {@code mean} may have any finite value (its only usage will be to
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* get multiplied by 0 to calculate the sum), and the other parameters may have any values
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* (they will not be used).
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* <li>If {@code count} is 1, {@code sumOfSquaresOfDeltas} must be exactly 0.0 or {@link
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* Double#NaN}.
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* </ul>
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*/
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Stats(long count, double mean, double sumOfSquaresOfDeltas, double min, double max) {
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this.count = count;
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this.mean = mean;
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this.sumOfSquaresOfDeltas = sumOfSquaresOfDeltas;
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this.min = min;
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this.max = max;
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}
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/**
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* Returns statistics over a dataset containing the given values.
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*
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* @param values a series of values, which will be converted to {@code double} values (this may
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* cause loss of precision)
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*/
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public static Stats ofIterable(Iterable<? extends Number> values) {
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StatsAccumulator accumulator = new StatsAccumulator();
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accumulator.addAll(values);
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return accumulator.snapshot();
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}
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/**
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* Returns statistics over a dataset containing the given values.
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*
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* @param values a series of values, which will be converted to {@code double} values (this may
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* cause loss of precision)
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*/
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public static Stats ofIterator(Iterator<? extends Number> values) {
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StatsAccumulator accumulator = new StatsAccumulator();
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accumulator.addAll(values);
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return accumulator.snapshot();
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}
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/**
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* Returns statistics over a dataset containing the given values.
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*
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* @param values a series of values
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*/
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public static Stats ofDoubles(double... values) {
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StatsAccumulator acummulator = new StatsAccumulator();
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acummulator.addAll(values);
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return acummulator.snapshot();
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}
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/**
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* Returns statistics over a dataset containing the given values.
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*
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* @param values a series of values
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*/
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public static Stats ofInts(int... values) {
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StatsAccumulator acummulator = new StatsAccumulator();
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acummulator.addAll(values);
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return acummulator.snapshot();
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}
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/**
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* Returns statistics over a dataset containing the given values.
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*
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* @param values a series of values, which will be converted to {@code double} values (this may
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* cause loss of precision for longs of magnitude over 2^53 (slightly over 9e15))
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*/
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public static Stats ofLongs(long... values) {
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StatsAccumulator acummulator = new StatsAccumulator();
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acummulator.addAll(values);
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return acummulator.snapshot();
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}
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/** Returns the number of values. */
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public long count() {
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return count;
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}
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private static final long serialVersionUID = 0;
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}

‎utbot-sample/src/main/java/guava/examples/math/StatsAccumulator.java

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/*
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* Copyright (C) 2012 The Guava Authors
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*
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* Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
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* in compliance with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software distributed under the License
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* is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
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* or implied. See the License for the specific language governing permissions and limitations under
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* the License.
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*/
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package guava.examples.math;
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import java.util.Iterator;
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import static java.lang.Double.*;
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public final class StatsAccumulator {
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// These fields must satisfy the requirements of Stats' constructor as well as those of the stat
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// methods of this class.
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private long count = 0;
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private double mean = 0.0; // any finite value will do, we only use it to multiply by zero for sum
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private double sumOfSquaresOfDeltas = 0.0;
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private double min = NaN; // any value will do
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private double max = NaN; // any value will do
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/** Adds the given value to the dataset. */
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public void add(double value) {
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if (count == 0) {
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count = 1;
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mean = value;
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min = value;
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max = value;
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if (!isFinite(value)) {
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sumOfSquaresOfDeltas = NaN;
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}
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} else {
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count++;
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if (isFinite(value) && isFinite(mean)) {
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// Art of Computer Programming vol. 2, Knuth, 4.2.2, (15) and (16)
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double delta = value - mean;
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mean += delta / count;
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sumOfSquaresOfDeltas += delta * (value - mean);
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} else {
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mean = calculateNewMeanNonFinite(mean, value);
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sumOfSquaresOfDeltas = NaN;
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}
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min = Math.min(min, value);
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max = Math.max(max, value);
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}
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}
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/**
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* Adds the given values to the dataset.
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*
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* @param values a series of values, which will be converted to {@code double} values (this may
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* cause loss of precision)
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*/
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public void addAll(Iterable<? extends Number> values) {
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for (Number value : values) {
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add(value.doubleValue());
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}
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}
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/**
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* Adds the given values to the dataset.
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*
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* @param values a series of values, which will be converted to {@code double} values (this may
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* cause loss of precision)
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*/
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public void addAll(Iterator<? extends Number> values) {
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while (values.hasNext()) {
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add(values.next().doubleValue());
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}
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}
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/**
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* Adds the given values to the dataset.
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*
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* @param values a series of values
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*/
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public void addAll(double... values) {
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for (double value : values) {
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add(value);
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}
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}
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/**
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* Adds the given values to the dataset.
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*
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* @param values a series of values
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*/
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public void addAll(int... values) {
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for (int value : values) {
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add(value);
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}
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}
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/**
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* Adds the given values to the dataset.
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*
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* @param values a series of values, which will be converted to {@code double} values (this may
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* cause loss of precision for longs of magnitude over 2^53 (slightly over 9e15))
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*/
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public void addAll(long... values) {
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for (long value : values) {
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add(value);
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}
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}
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/** Returns an immutable snapshot of the current statistics. */
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public Stats snapshot() {
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return new Stats(count, mean, sumOfSquaresOfDeltas, min, max);
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}
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/** Returns the number of values. */
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public long count() {
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return count;
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}
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/**
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* Calculates the new value for the accumulated mean when a value is added, in the case where at
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* least one of the previous mean and the value is non-finite.
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*/
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static double calculateNewMeanNonFinite(double previousMean, double value) {
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/*
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* Desired behaviour is to match the results of applying the naive mean formula. In particular,
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* the update formula can subtract infinities in cases where the naive formula would add them.
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*
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* Consequently:
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* 1. If the previous mean is finite and the new value is non-finite then the new mean is that
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* value (whether it is NaN or infinity).
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* 2. If the new value is finite and the previous mean is non-finite then the mean is unchanged
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* (whether it is NaN or infinity).
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* 3. If both the previous mean and the new value are non-finite and...
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* 3a. ...either or both is NaN (so mean != value) then the new mean is NaN.
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* 3b. ...they are both the same infinities (so mean == value) then the mean is unchanged.
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* 3c. ...they are different infinities (so mean != value) then the new mean is NaN.
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*/
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if (isFinite(previousMean)) {
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// This is case 1.
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return value;
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} else if (isFinite(value) || previousMean == value) {
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// This is case 2. or 3b.
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return previousMean;
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} else {
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// This is case 3a. or 3c.
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return NaN;
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}
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}
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public static boolean isFinite(double value) {
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return NEGATIVE_INFINITY < value && value < POSITIVE_INFINITY;
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}
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}

‎utbot-summary-tests/build.gradle

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apply from: "${parent.projectDir}/gradle/include/jvm-project.gradle"
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apply plugin: "java"
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evaluationDependsOn(':utbot-framework')
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compileTestJava.dependsOn tasks.getByPath(':utbot-framework:testClasses')
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dependencies {
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implementation(project(":utbot-framework"))
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implementation(project(':utbot-instrumentation'))
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testImplementation project(':utbot-sample')
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testImplementation group: 'junit', name: 'junit', version: junit4_version
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testCompile project(':utbot-framework').sourceSets.test.output
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}
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test {
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useJUnitPlatform()
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}

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