Multi-Objective ANT Lion Optimization Algorithm Based Mutant Test Case Selection for Regression Testing

582-592The regression testing is principally carried out on modified parts of the programs. The quality of programs is the only concern of regression testing in the case of produced software. Main challenges to select mutant test cases are related to the affected classes. In software regression testing, the identification of optimal mutant test case is another challenge. In this research work, an evolutionary approach multi objective ant-lion optimization (MOALO) is proposed to identify optimal mutant test cases. The selection of mutant test cases is processed as multi objective enhancement problem and these will solve through MOALO algorithm. Optimal identification of mutant test cases is carried out by using the above algorithm which also enhances the regression testing efficiency. The proposed MOALO methods are implemented and tested using the Mat Lab software platform. On considering the populace size of 100, at that point the fitness estimation of the proposed framework, NSGA, MPSO, and GA are 3, 2.4, 1, and 0.3 respectively. The benefits and efficiencies of proposed methods are compared with random testing and existing works utilizing NSGA-II, MPSO, genetic algorithms in considerations of test effort, mutation score, fitness value, and time of execution. It is found that the execution times of MOALO, NSGA, MPSO, and GA are 2.8, 5, 6.5, and 7.8 respectively. Finally, it is observed that MOALO has higher fitness estimation with least execution time which indicates that MOALO methods provide better results in regression testing

Multi-Objective ANT Lion Optimization Algorithm Based Mutant Test CaseSelection for Regression Testing

The regression testing is principally carried out on modified parts of the programs. The quality of programs is the only concern of regression testing in the case of produced software. Main challenges to select mutant test cases are related to the affected classes. In software regression testing, the identification of optimal mutant test case is another challenge. In this research work, an evolutionary approach multi objective ant-lion optimization (MOALO) is proposed to identify optimal mutant test cases. The selection of mutant test cases is processed as multi objective enhancement problem and these willsolve through MOALO algorithm. Optimal identification of mutant test cases is carried out by using the above algorithm which also enhances the regression testing efficiency. The proposed MOALO methods are implemented and tested using the Mat Lab software platform. On considering the populace size of 100, at that point the fitness estimation of the proposed framework, NSGA, MPSO, and GA are 3, 2.4, 1, and 0.3 respectively. The benefits and efficiencies of proposed methods are compared with random testing and existing works utilizing NSGA-II, MPSO, genetic algorithms in considerations of test effort, mutation score, fitness value, and time of execution. It is found that the execution times of MOALO, NSGA, MPSO, and GA are 2.8, 5, 6.5, and 7.8 respectively. Finally, it is observed that MOALO has higher fitness estimation with least execution time which indicates that MOALO methods provide better results in regression testing

Testitapausten testikattavuuden riittämättömyys

Tiivistelmä. Testitapausten luonti on keskeisessä roolissa ohjelmistotestauksessa. Tämä pätee niin testauksen toteutukselle, tutkimukselle kuin myös muulle alan teoreettiselle pohjalle. Testaus on hyvin pitkälti rakentunut testitapausten ympärille. Aiempi tutkimus on havainnut testitapauksilla testattaessa myös löytyvän sellaisia ohjelmistovirheitä, jotka eivät ole testitapausten määräämällä ohjelman alueella. Testitapauksia käytettäessä testauksessa, ne määräävät testattavasta ohjelmasta toiminnallisuuksien ja ominaisuuksien alueen, jota testit koskevat. Silloin on myös oltava ohjelman alue, joita testitapaukset eivät koske, ts., testitapausten ulkopuolinen alue. Testitapausten käsikirjoituksen määräämä testikattavuus ei siis välttämättä täysin vastaa toteutunutta testauksen laajuutta, kun testitapausten joukon testit ajetaan manuaalisesti. Tämän opinnäytetyön tarkoituksena on tutkia tätä testitapausten testikattavuuden ulkopuolisten virheiden ilmiötä. Näin kaksi tutkimuskysymystä on esitetty: ”Kuinka suuri osa käsikirjoitetun testauksen löytämistä ohjelmistovirheistä ovat käsikirjoitettujen testitapausten kattamia?” sekä ”Vaikuttaako testitapausten testausohjeistuksen rakenne ulkopuolisten virheiden esiintymiseen?” Näihin kysymyksiin vastaamiseksi järjestettiin aikarajoitettu opiskelijoilla tehtävä koe manuaalisesta funktionaalisesti käsikirjoitetusta testauksesta, joka pohjautui ennalta luotuihin testitapauksiin. Testikattavuuden yksiköitä usein luonnehditaan riittämättömäksi täysin kattavalle testaukselle, mutta tämän kokeen tulokset tuo tarkastelun alle vielä toisenlaisen ongelman testikattavuudesta: vaikka testitapausten määräämä testikattavuus olisi riittävä, se ei kuitenkaan välttämättä realisoidu riittävinä testauksen tuloksina. Vain osa virheistä löytyivät, jotka olisi pitänyt testitapauksia testaamalla löytää. Tämän lisäksi merkittävä osuus löytyneistä virheistä eivät olleet testitapausten kattamalla alueella. Testitapausten ulkopuolinen olisi tiedostettava ja huomioitava paremmin. Sen huomiotta jättäminen ja testitapauksiin sokea luottaminen saattaa aiheuttaa ongelmia ja ylimääräisiä kustannuksia ohjelmistoalalla.The insufficiency of test case test coverage. Abstract. The creation of test cases is in a central role in software testing. This applies to software testing in the software industry as well as its’ research and other theoretical basis. Testing is largely based on test cases. Prior research conducted on test case-based testing has noted that the testing process discovers defects from the tested software which are not covered by the test cases’ script, i.e., defects external to the test cases’ coverage. When test cases are used in testing, they determine an area from the functionalities and other features of the software which the tests cover. This also means that there should exist an area outside this coverage: the external area of test coverage. The purpose of this thesis is to study the phenomenon of the discovery of external defects of test case test coverage. Thus, two research questions have been formed as follows: “How large part of the defects found by scripted testing are covered by the test coverage of the script?” and “Does the structure of the test script affect the emergence of external defects of the test case test coverage?” To answer these questions an experiment of scripted testing was conducted with students as participants. While the metrics of test coverage are often described as insufficient for complete testing, yet, as a result of this thesis, another issue of test coverage is brought upon inspection: even if the test coverage was sufficient; the testing conducted to achieve the coverage does not necessarily actualize as sufficient. Only a part of the defects were found with the tests which cover the defects and, in addition to this, a portion of the defects found by testing the test script are not actually covered by the script. The external of the test case should be acknowledged and noted in greater detail. The ignorance of the external and blind reliance on a test script may cause troubles and extra costs in the field of software testing

Customer Service Strategies to Minimize Negative Customer Incidents in the Airline Industry

There has been a continuous increase in customer complaints against airlines in the United States. The airlines’ customer service complaints were up 90% in April 2017 compared to April 2016. Airline customer service managers who do not address customer complaints may experience reduced customer satisfaction, customer retention, and profitability. Grounded in the service quality model, the purpose of this qualitative multiple case study was to explore customer service strategies airline customer service managers use to mitigate negative customer incidents. Participants were three airline customer service managers from two airlines who developed strategies to minimize negative customer incidents. Data were collected from semistructured interviews, company documents, and social media platforms. Yin’s five-step data analysis approach was used to analyze the data. Five themes emerged: recruit competent employees, enhance training, strengthen communication, elicit customer feedback, and improve service policies and standards. A key recommendation is for customer service managers to develop and implement robust training to empower frontline personnel with education and skills to improve service quality and mitigate customer complaints. The implications for positive social change include potentially mitigating unpleasant customer experiences, cultivating trust and loyalty between the airlines and the travel community, and increasing customer satisfaction