{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T18:46:38Z","timestamp":1769712398343,"version":"3.49.0"},"reference-count":17,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2023,4,3]]},"abstract":"<jats:p>The software development and maintenance phase succeeded with significant regression testing activity. The software must be re-tested every time it upgrades to preserve its quality. Software testing as a whole is an expensive and tedious task due to resource constraints. Using the prioritization technique implies regression testing to re-test software after it has been modified. In this situation, the prioritization technique can use information acquired about earlier test case executions to generate test case orderings. The approaches for test case prioritization arrange them all in such a sequence that maximizes their efficacy in accomplishing specific goals. This paper presents a hybrid technique for change-testing or regression testing through test case prioritization. The suggested method first generates the test cases, then clustered in untested and unimportant groups using kernel-based fuzzy c-means clustering technique. The appropriate test cases are then considered for prioritization using the grey wolf optimizer. The results compared with the approaches such as ant colony, particle swarm, and genetic algorithm optimization method, and it is observed that the proposed approach efficiency increased by 91% of fault detection rate.<\/jats:p>","DOI":"10.3233\/jifs-222433","type":"journal-article","created":{"date-parts":[[2022,12,30]],"date-time":"2022-12-30T11:40:20Z","timestamp":1672400420000},"page":"5711-5718","source":"Crossref","is-referenced-by-count":4,"title":["Test case prioritization for changed code using nature inspired optimizer"],"prefix":"10.1177","volume":"44","author":[{"given":"Babita","family":"Pathik","sequence":"first","affiliation":[{"name":"Department of CSE, TIT, Bhopal, India"}]},{"given":"Nikhlesh","family":"Pathik","sequence":"additional","affiliation":[{"name":"Department of CSE, ASET, Amity University, Gwalior, India"}]},{"given":"Meena","family":"Sharma","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, IET, DAVV, Indore, India"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-222433_ref1","unstructured":"Glenford Myers J. , Art of Software Testing, John Wiley & Sons, Inc., USA, 1979."},{"key":"10.3233\/JIFS-222433_ref2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10515-021-00305-x","article-title":"Source code change analysis with deep learning based programming model","volume":"29","author":"Pathik","year":"2022","journal-title":"Automated Software Engineering"},{"key":"10.3233\/JIFS-222433_ref3","first-page":"975","article-title":"A genetic algorithm for fault based regression test case prioritization","volume":"32","author":"Arvinder Kaur","year":"2011","journal-title":"International Journal of Computer Applications"},{"key":"10.3233\/JIFS-222433_ref5","unstructured":"Muhammad Khatibsyarbini , Mohd Adham Isa and Abang Jawawi D.N. , A Hybrid Weight-Based and String Distances Using Particle Swarm Optimization for Prioritizing Test Cases, Journal of Theoretical & Applied Information Technology 95(12) (2017)."},{"key":"10.3233\/JIFS-222433_ref7","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","article-title":"Grey wolf optimizer","volume":"69","author":"Seyedali Mirjalili","year":"2014","journal-title":"Advances in Engineering Software"},{"key":"10.3233\/JIFS-222433_ref8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.17485\/ijst\/2015\/v8i35\/81102","article-title":"Combined genetic and simulated annealing approach for test case prioritization","volume":"8","author":"Uma Maheswari","year":"2015","journal-title":"Indian Journal of Science and Technology"},{"key":"10.3233\/JIFS-222433_ref11","doi-asserted-by":"crossref","first-page":"132360","DOI":"10.1109\/ACCESS.2019.2940620","article-title":"Test case prioritization using firefly algorithm for software testing","volume":"7","author":"Muhammad Khatibsyarbini","year":"2019","journal-title":"IEEE 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