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              <text>Test case reduction and SWOA optimization for distributed agile software development using regression testing</text>
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          <name>Subject</name>
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              <text>Fractional Sigmoid based K-means Clustering; Regression Testing; Support-based Whale Optimization Algorithm; Test Case Reduction</text>
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              <text>Regression testing is a well-established practice in software development, but its position and importance have shifted in recent years as agile approaches have grown in popularity, emphasizing the fundamental role of regression testing in preserving software quality. In previous techniques, the challenge to address is determining the number and size of clusters and optimization to stabilize the cost and efficacy of the strategy. To overcome all the existing drawbacks; this research study proposes test case reduction and Support-based Whale Optimization Algorithm (SWOA) for distributed agile software development using regression testing. The purpose of this research study is to look into regression testing strategies in agile development teams and to find out what they are optimum clustered test cases. The proposed strategy is divided into two stages: prioritization as well as selection. Prioritization and selection are carried out once the test instances have been retrieved and grouped. The test case clusters are sorted and prioritized in this stage to ensure that the most critical instances are chosen first. During this stage, the test case clusters undergo sorting and prioritization to guarantee that the most essential cases are selected initially. Second, the SWOA is used to choose test cases with a greater frequency of failure or coverage criterion. The results of the assessment metrics show that the proposed approach outperforms other current regression testing strategies substantially. Based on experimental findings, our proposed approach betters existing methods in terms of information performance.  The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.</text>
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              <text>Singh M.; Chauhan N.; Popli R.</text>
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              <text>Multimedia Tools and Applications</text>
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              <text>2024-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1007/s11042-024-19148-1" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s11042-024-19148-1&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191069462&amp;amp;doi=10.1007%2Fs11042-024-19148-1&amp;amp;partnerID=40&amp;amp;md5=82b6fedd08d718b6456bd20af841193d" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191069462&amp;amp;doi=10.1007%2fs11042-024-19148-1&amp;amp;partnerID=40&amp;amp;md5=82b6fedd08d718b6456bd20af841193d&lt;/a&gt;</text>
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              <text>All Open Access; Green Open Access</text>
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              <text>ISSN: 13807501; CODEN: MTAPF</text>
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              <text>Singh M., Christ (Deemed to be University) Delhi NCR Campus, Uttar Pradesh, Ghaziabad, India; Chauhan N., Department of Computer Engineering at JC Bose University of Science &amp;amp; amp; Technology, Faridabad, India; Popli R., J. C. Bose University of Science and Technology, YMCA, Faridabad, India</text>
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