Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Multi-objective ANT lion optimization algorithm based mutant test case selection for regression testing Subject The topic of the resource Genetic algorithm; Matlab; Mutant test case; Regression testing; Software testing Description An account of the resource 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 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. 2021 Scientific Publishers. All rights reserved. Creator An entity primarily responsible for making the resource Tripathi A.; Srivastava S.; Mittal H.; Sinha S.; Yadav V. Source A related resource from which the described resource is derived Journal of Scientific and Industrial Research, Vol-80, No. 7, pp. 582-592. Publisher An entity responsible for making the resource available National Institute of Science Communication and Information Resources Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116109051&amp;partnerID=40&amp;md5=4364c82591b63310aa68949ba64a73f1" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116109051&amp;partnerID=40&amp;md5=4364c82591b63310aa68949ba64a73f1</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 224456 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Tripathi A., VIT Bhopal University, Madhya Pradesh, India; Srivastava S., Christ University, India; Mittal H., Raj Kumar Goel Institute of Technology, Uttar Pradesh, Ghaziabad, India; Sinha S., JSS Academy of Technical Education, Uttar Pradesh, Noida, India; Yadav V., ABES Engineering College, Uttar Pradesh, Ghaziabad, India