// 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.UsabilityDefect; 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()); } }