Quantum Machine Learning Techniques Integrated in Quantum Software Testing

Quantum Machine Learning Techniques Integrated in Quantum Software Testing | 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 Quantum Machine Learning Techniques Integrated in Quantum Software Testing Bala Gangadhara Gutam, Sunil Kumar Malchi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4653367/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Quantum computing (QC) is the era of the mechanisms that quantum solves complex problems faster than classical computers (CCs). Today, there are more opportunities for the public and private sectors to use high-value quantum solutions. QC relies on quantum phenomena to calculate incredible speeds and set for significant expansion. Quantum computers, QC-based Internet of Things (IoT), and communication devices to create, process, and transmit quantum states and entanglement are anticipated to enhance society’s quantum software. In this context, this paper introduces the Quantum Software Testing (QST) approach with Machine Learning (ML) techniques integrated into the Quantum Software Testing Life Cycle (QSTLC). The proposed Quantum Machine Learning Testing (QMLT) exploits ML techniques at critical stages of the QST to enhance testing efficiency, accuracy, and adaptability. Finally, the proposed automated test report generation, summarizing, and knowledge extraction technique facilitates comprehensive documentation and knowledge transfer. Quantum Computing Software Testing Life Cycle Software Development Phases Machine Learning Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version 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-4653367","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":328522584,"identity":"3599dde3-ed1e-48f7-8a95-f9b2c19ebb3d","order_by":0,"name":"Bala Gangadhara Gutam","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIiWNgGAWjYBACAwbmBmYo2wyIbYCYsfEAfi2MKFrSQFoaSNJyGMzCq8Wc/WDj54Jfdnny7oe3Pfi557zd2vbDQFtqbKJxabHsSWyWntmXXGx4Jq3csOfZ7eRtZxKBWo6l5TbgctiBxAZp3h7mxI0NOWYSPAduJ5sBRQ4wNhzGreX8w+bfvD31iRv735hJ/jlwLtns/EMCWm4ktknz/DicOF8ix0ya58ABO7MbBGyxnPGwzXpmw/HEDRLPyqRlDiQnmN0A2pKAxy/m/MmHbxf8qU6c35+8TfLNATt7s/PpDx98qLHBqQUMGNtA4QBhJ4JVJuBTDgZ/GBjkoYbaE1Q8CkbBKBgFIw4AADujbKdreobzAAAAAElFTkSuQmCC","orcid":"","institution":"Mohan Babu University","correspondingAuthor":true,"prefix":"","firstName":"Bala","middleName":"Gangadhara","lastName":"Gutam","suffix":""},{"id":328522589,"identity":"fbc1a628-b428-49cd-9bb0-78f9cf88ea69","order_by":1,"name":"Sunil Kumar Malchi","email":"","orcid":"","institution":"Mohan Babu University","correspondingAuthor":false,"prefix":"","firstName":"Sunil","middleName":"Kumar","lastName":"Malchi","suffix":""}],"badges":[],"createdAt":"2024-06-28 08:44:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4653367/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4653367/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62495673,"identity":"b371a63e-20db-4d3c-9c50-5ec05436a5a6","added_by":"auto","created_at":"2024-08-14 23:07:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":429534,"visible":true,"origin":"","legend":"","description":"","filename":"QuantumManuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4653367/v1_covered_a54fd7b9-f76c-4a99-ba94-f4b6bfa5081a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Quantum Machine Learning Techniques Integrated in Quantum Software Testing","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":"Quantum Computing, Software Testing Life Cycle, Software Development Phases, Machine Learning","lastPublishedDoi":"10.21203/rs.3.rs-4653367/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4653367/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Quantum computing (QC) is the era of the mechanisms that quantum solves complex problems faster than classical computers (CCs). 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