// Copyright 2012 Georg-August-Universität Göttingen, Germany
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package de.ugoe.cs.autoquest.usability.rules.metrics;
import static de.ugoe.cs.autoquest.usability.testutil.FestConditionUtil.absent;
import static de.ugoe.cs.autoquest.usability.testutil.FestConditionUtil.highRecommendationSeverityLevel;
import static de.ugoe.cs.autoquest.usability.testutil.FestConditionUtil.infoRecommendationSeverityLevel;
import static de.ugoe.cs.autoquest.usability.testutil.FestConditionUtil.lowRecommendationSeverityLevel;
import static de.ugoe.cs.autoquest.usability.testutil.FestConditionUtil.mediumRecommendationSeverityLevel;
import static de.ugoe.cs.autoquest.usability.testutil.FestConditionUtil.present;
import static org.fest.assertions.api.Assertions.assertThat;
import org.junit.Test;
import com.google.common.base.Optional;
import de.ugoe.cs.autoquest.tasktrees.treeifc.ITaskModel;
import de.ugoe.cs.autoquest.usability.result.UsabilityProblemDescription;
import de.ugoe.cs.autoquest.usability.testutil.GenerateTaskModelUtil;
/**
*
* TODO comment
*
*
* @author Alexander Deicke
*/
public class TextInputEntryRepetitionsEvaluatorTest {
@Test
public void should_return_no_recommendation() {
// Given
String spec = "UserSession {" +
" Sequence seq1 {" +
" TextInput t1 () {}" +
" }" +
"}";
ITaskModel taskTree = GenerateTaskModelUtil.getTaskModelFromSpec(spec);
// When
Optional recommendation = new TextInputEntryRepetitionsMetric(taskTree).calculate();
// Then
assertThat(recommendation).is(absent());
}
@Test
public void should_return_recommendation_with_info_severity_level() {
// Given
String spec = "UserSession {" +
" Sequence seq1 {" +
" TextInput t1 (a b c) {}" +
" Sequence seq2 {" +
" TextInput t2 (a) {}" +
" TextInput t3 (d) {}" +
" TextInput t4 (e) {}" +
" }" +
" }" +
"}";
ITaskModel taskTree = GenerateTaskModelUtil.getTaskModelFromSpec(spec);
// When
Optional recommendation = new TextInputEntryRepetitionsMetric(taskTree).calculate();
// Then
assertThat(recommendation).is(present()).has(infoRecommendationSeverityLevel());
}
@Test
public void should_return_recommendation_with_low_severity_level() {
// Given
String spec = "UserSession {" +
" Sequence seq1 {" +
" TextInput t1 (a b c) {}" +
" Sequence seq3 {" +
" TextInput t2 (a) {}" +
" TextInput t3 (b) {}" +
" TextInput t4 (c) {}" +
" }" +
" }" +
"}";
ITaskModel taskTree = GenerateTaskModelUtil.getTaskModelFromSpec(spec);
// When
Optional recommendation = new TextInputEntryRepetitionsMetric(taskTree).calculate();
// Then
assertThat(recommendation).is(present()).has(lowRecommendationSeverityLevel());
}
@Test
public void should_return_recommendation_with_medium_severity_level() {
// Given
String spec = "UserSession {" +
" Sequence seq1 {" +
" TextInput t1 (a b c d e f g h i j k l m) {}" +
" Sequence seq2 {" +
" TextInput t2 (a) {}" +
" TextInput t3 (b) {}" +
" TextInput t4 (c) {}" +
" TextInput t5 (d) {}" +
" }" +
" Iteration iter1 {" +
" TextInput t6 (e) {}" +
" }" +
" TextInput t7 (a) {}" +
" Selection sel1 {" +
" TextInput t8 (b) {}" +
" }" +
" Selection sel1 {" +
" TextInput t8 (c) {}" +
" }" +
" Selection sel1 {" +
" TextInput t8 (d) {}" +
" }" +
" Selection sel1 {" +
" TextInput t8 (e) {}" +
" }" +
" Sequence seq3 {" +
" TextInput t9 (a) {}" +
" Sequence seq4 {" +
" TextInput t10 (b) {}" +
" TextInput t11 (c) {}" +
" TextInput t12 (d) {}" +
" TextInput t13 (e) {}" +
" }" +
" }" +
" TextInput t14 (a) {}" +
" }" +
"}";
ITaskModel taskTree = GenerateTaskModelUtil.getTaskModelFromSpec(spec);
// When
Optional recommendation = new TextInputEntryRepetitionsMetric(taskTree).calculate();
// Then
assertThat(recommendation).is(present()).has(mediumRecommendationSeverityLevel());
}
@Test
public void should_return_recommendation_with_high_severity_level() {
// Given
String spec = "UserSession {" +
" Sequence seq1 {" +
" TextInput t1 (a b c) {}" +
" Sequence seq2 {" +
" TextInput t2 (a) {}" +
" TextInput t3 (b) {}" +
" TextInput t4 (c) {}" +
" TextInput t5 (a) {}" +
" }" +
" Iteration iter1 {" +
" TextInput t6 (a) {}" +
" }" +
" TextInput t7 (a) {}" +
" Selection sel1 {" +
" TextInput t8 (b c) {}" +
" }" +
" Selection sel1 {" +
" TextInput t8 (a) {}" +
" }" +
" Selection sel1 {" +
" TextInput t8 (a c) {}" +
" }" +
" Selection sel1 {" +
" TextInput t8 (b a) {}" +
" }" +
" Sequence seq3 {" +
" TextInput t9 (b c) {}" +
" Sequence seq4 {" +
" TextInput t10 (d a c) {}" +
" TextInput t11 (b b b a) {}" +
" TextInput t12 (a a c c) {}" +
" TextInput t13 (b b a) {}" +
" }" +
" }" +
" TextInput t14 (a) {}" +
" }" +
"}";
ITaskModel taskTree = GenerateTaskModelUtil.getTaskModelFromSpec(spec);
// When
Optional recommendation = new TextInputEntryRepetitionsMetric(taskTree).calculate();
// Then
assertThat(recommendation).is(present()).has(highRecommendationSeverityLevel());
}
}