­Automated Generation of Covering Array Using Gravitational Search Algorithm and Biogeography Based Optimization

­Automated Generation of Covering Array Using Gravitational Search Algorithm and Biogeography Based Optimization | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article ­Automated Generation of Covering Array Using Gravitational Search Algorithm and Biogeography Based Optimization Sajad Esfandyari, liela Yousofvand, Vahid Rafe, Einollah Pira This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3706348/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract The utilization of combinatorial testing methodologies in software development has become widespread, necessitating the development of efficient strategies for creating high-quality test suites. Covering Array (CA) has emerged as a key component of combinatorial testing, offering various types to fulfill diverse testing requirements. Several strategies have been introduced for generating CAs, each with its own strengths and weaknesses in terms of performance and efficiency. However, there is still a gap in the existence of a strategy that effectively addresses both aspects simultaneously. Moreover, manually collecting software information increases the likelihood of errors and presents challenges due to the complexity of extracting relevant data. To tackle these challenges, this study employs the GROOVE model checker to automate the extraction of variables and their interactions within the software. By adapting the Gravitational Search Algorithm (GSA) and Biogeography Based Optimization (BBO), an optimal test suite is generated with enhanced efficiency. The primary objective of this paper is to develop a software model using the GROOVE model checker and utilize its capabilities to extract essential software information. The proposed methodology utilizes GSA and BBO to create CAs with both uniform and variable strength. Additionally, a mechanism is introduced to expedite search operations within data structures. To assess the efficacy of the proposed approach, it is implemented within the GROOVE environment, alongside various other meta-heuristic algorithms. Furthermore, the proposed algorithm is also externally implemented for comparison with existing strategies. The evaluation results indicate that the proposed solution surpasses other strategies in terms of efficiency and performance. Gravitational Search Algorithm (GSA) Biogeography Based Optimization(BBO) Covering Array Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3706348","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":273940829,"identity":"00ea7c33-c22a-4360-84c1-e1ddb6f67be0","order_by":0,"name":"Sajad Esfandyari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYHCCBAYeBgYeefb+jw+APB4+YrXIGPYcMDYAaWEjyh6gFhuGGw5mEiAOQS3y7QcefnjDYMfDOIMhrfJrjp0MGwPzw0c38GgxOJOQLDmHIZmHXbrh2G3ZbclAh7EZG+fg08KQkCDNw8DMwzjnYNttyW3MQC08bNL4tMj3P0j+zcNQz8NwI5mtWHJbPWEtDDcS0oC2HAZqSWNj/LjtMGEtBjcepFnOMTjOY9hzhlmacdtxHjZmAn6R789JvvGmotpenr2H8ePPbdX2/OzNDx/jdRgDTwIoEMCAmQdM4lUOAuwH4EzGHwRVj4JRMApGwUgEAPh1QkB1VKEaAAAAAElFTkSuQmCC","orcid":"","institution":"Malayer University","correspondingAuthor":true,"prefix":"","firstName":"Sajad","middleName":"","lastName":"Esfandyari","suffix":""},{"id":273940832,"identity":"10c95542-d0c9-4330-9ff7-9272b528a480","order_by":1,"name":"liela Yousofvand","email":"","orcid":"","institution":"Arak University","correspondingAuthor":false,"prefix":"","firstName":"liela","middleName":"","lastName":"Yousofvand","suffix":""},{"id":273940830,"identity":"1c1fe41d-6c1e-4c70-a8a7-7f23362a6dac","order_by":2,"name":"Vahid Rafe","email":"","orcid":"","institution":"Arak University","correspondingAuthor":false,"prefix":"","firstName":"Vahid","middleName":"","lastName":"Rafe","suffix":""},{"id":273940831,"identity":"d115e01d-29c2-4787-b32d-d16017e2be36","order_by":3,"name":"Einollah Pira","email":"","orcid":"","institution":"Azarbaijan Shahid Madani University","correspondingAuthor":false,"prefix":"","firstName":"Einollah","middleName":"","lastName":"Pira","suffix":""}],"badges":[],"createdAt":"2023-12-04 16:44:26","currentVersionCode":2,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-3706348/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-3706348/v2","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52443329,"identity":"90d46a42-ea47-4e8c-9a1c-26ebf1bbbaa9","added_by":"auto","created_at":"2024-03-11 17:34:15","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1056564,"visible":true,"origin":"","legend":"","description":"","filename":"VSCA1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3706348/v2_covered_e5d35b8d-0fae-4145-9a09-5df4fb83569f.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003e­Automated Generation of Covering Array Using Gravitational Search Algorithm and Biogeography Based Optimization\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Gravitational Search Algorithm (GSA), Biogeography Based Optimization(BBO), Covering Array","lastPublishedDoi":"10.21203/rs.3.rs-3706348/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3706348/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe utilization of combinatorial testing methodologies in software development has become widespread, necessitating the development of efficient strategies for creating high-quality test suites. 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