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The most important challenge of any software developer is that ‘the software should be 100% accurate or with minimal defect’ when it reaches to the end-user. The earlier" /> <meta name="twitter:image" content="https://0.academia-photos.com/99080811/27084024/25503717/s200_tripti.gautam.jpg" /> <meta property="fb:app_id" content="2369844204" /> <meta property="og:type" content="article" /> <meta property="og:url" content="https://www.academia.edu/78837169/Optimal_Metrics_Selection_for_Software_Defect_Prediction" /> <meta property="og:title" content="Optimal Metrics Selection for Software Defect Prediction" /> <meta property="og:image" content="http://a.academia-assets.com/images/open-graph-icons/fb-paper.gif" /> <meta property="og:description" content="Software metrics are a very important component in software development area. The most important challenge of any software developer is that ‘the software should be 100% accurate or with minimal defect’ when it reaches to the end-user. 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The earlier" /> <meta name="robots" content="noindex" /> <title>Optimal Metrics Selection for Software Defect Prediction | Tripti Gautam - Academia.edu</title> <link rel="canonical" href="https://www.academia.edu/78837169/Optimal_Metrics_Selection_for_Software_Defect_Prediction" /> <script async src="https://www.googletagmanager.com/gtag/js?id=G-5VKX33P2DS"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-5VKX33P2DS', { cookie_domain: 'academia.edu', send_page_view: false, }); gtag('event', 'page_view', { 'controller': "single_work", 'action': "show", 'controller_action': 'single_work#show', 'logged_in': 'false', 'edge': 'unknown', // Send nil if there is no A/B test bucket, in case some records get logged // with missing data - that way we can distinguish between the two cases. // ab_test_bucket should be of the form <ab_test_name>:<bucket> 'ab_test_bucket': null, }) </script> <script> var $controller_name = 'single_work'; var $action_name = "show"; var $rails_env = 'production'; var $app_rev = '49879c2402910372f4abc62630a427bbe033d190'; var $domain = 'academia.edu'; var $app_host = "academia.edu"; var $asset_host = "academia-assets.com"; var $start_time = new Date().getTime(); var $recaptcha_key = "6LdxlRMTAAAAADnu_zyLhLg0YF9uACwz78shpjJB"; var $recaptcha_invisible_key = "6Lf3KHUUAAAAACggoMpmGJdQDtiyrjVlvGJ6BbAj"; var $disableClientRecordHit = false; </script> <script> window.require = { config: function() { return function() {} } } </script> <script> window.Aedu = window.Aedu || {}; window.Aedu.hit_data = null; window.Aedu.serverRenderTime = new Date(1732429347000); window.Aedu.timeDifference = new Date().getTime() - 1732429347000; </script> <script type="application/ld+json">{"@context":"https://schema.org","@type":"ScholarlyArticle","abstract":"Software metrics are a very important component in software development area. The most important challenge of any software developer is that ‘the software should be 100% accurate or with minimal defect’ when it reaches to the end-user. The earlier the defect is detected, the earlier the development cost also gets reduced. This is a fact that more complex the data or software, there is a more probability of the defect. So it is always desirable to use only the relevant and important data for the software development which will definitely reduce time and cost of the developer. The main objective of this paper is to find the important and relevant metrics in the software modules which will reduce the attribute in a data set. More the number of variables, more complex will be the system and more the defects; so it is always preferable to select the small feature set using feature selection and focus only on the important variable. The data set for the software bug prediction Chidamber and Kemerer metrics and Object Oriented metrics were taken from the Promise repository which is publicly available. The experiment from the 10 software modules (Jureczko M. Software Engineering: An International Journal 2011;1(1):95), ant, ivy, tomcat, berek, camel, jedit, lucene, poi, synapse and velocity, using feature selection techniques, Boruta, regsubset and FSelector, has shown that response for a class, lines of code and weighted methods for class are the most optimal metrics, whereas number of children and Depth of Inheritance Tree are least significant.","author":[{"@context":"https://schema.org","@type":"Person","name":"Tripti Gautam"}],"contributor":[],"dateCreated":"2022-05-09","dateModified":null,"datePublished":"2017-01-01","headline":"Optimal Metrics Selection for Software Defect Prediction","inLanguage":"en","keywords":[],"locationCreated":null,"publication":"International Journal of Data Mining and Emerging Technologies","publisher":{"@context":"https://schema.org","@type":"Organization","name":"Diva Enterprises Private Limited"},"image":null,"thumbnailUrl":null,"url":"https://www.academia.edu/78837169/Optimal_Metrics_Selection_for_Software_Defect_Prediction","sourceOrganization":[{"@context":"https://schema.org","@type":"EducationalOrganization","name":"ggsipu"}]}</script><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/single_work_page/loswp-352e32ba4e89304dc0b4fa5b3952eef2198174c54cdb79066bc62e91c68a1a91.css" /><link crossorigin="" href="https://fonts.gstatic.com/" rel="preconnect" /><link href="https://fonts.googleapis.com/css2?family=DM+Sans:ital,opsz,wght@0,9..40,100..1000;1,9..40,100..1000&family=Gupter:wght@400;500;700&family=IBM+Plex+Mono:wght@300;400&family=Material+Symbols+Outlined:opsz,wght,FILL,GRAD@20,400,0,0&display=swap" rel="stylesheet" /><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/design_system/common-10fa40af19d25203774df2d4a03b9b5771b45109c2304968038e88a81d1215c5.css" /> </head> <body> <div id='react-modal'></div> <div 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The most important challenge of any software developer is that ‘the software should be 100% accurate or with minimal defect’ when it reaches to the end-user. The earlier the defect is detected, the earlier the development cost also gets reduced. This is a fact that more complex the data or software, there is a more probability of the defect. So it is always desirable to use only the relevant and important data for the software development which will definitely reduce time and cost of the developer. The main objective of this paper is to find the important and relevant metrics in the software modules which will reduce the attribute in a data set. More the number of variables, more complex will be the system and more the defects; so it is always preferable to select the small feature set using feature selection and focus only on the important variable. 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window.loswp.useOptimizedScribd4genScript = false; window.loswp.appleClientId = 'edu.academia.applesignon';</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="loswp-grid--container"><div data-auto_select="false" data-client_id="331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b" data-landing_url="https://www.academia.edu/78837169/Optimal_Metrics_Selection_for_Software_Defect_Prediction" data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" id="g_id_onload"></div><div class="above-fold js-swp-splash-above-fold"><div class="work-card--container js-swp-control-work-card" data-entity-id="78837169"><div class="work-cover--wrapper"><div class="work-cover--container"><div class="work-cover--no-attachment-container js-swp-splash-paper-cover"><div class="work-cover--file-icon-wrapper"><img alt="paper cover icon" src="//a.academia-assets.com/images/single_work_splash/adobe.icon.svg" /></div><div class="work-cover--title js-swp-splash-paper-cover-page-title">Optimal Metrics Selection for Software Defect Prediction</div><br /><div style="margin-top: 170px"><button class="work-cover--request-pdf-button js-request-pdf-button"><svg style="width: 14px; 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font-weight: 500; color: #4b4b4b;"><div class="u-textTruncate"><span itemprop="author">Tripti Gautam</span></div></div></a><script data-card-contents-for-user="99080811" type="text/json">{"id":99080811,"first_name":"Tripti","middle_initials":null,"last_name":"Gautam","page_name":"TriptiGautam","domain_name":"ggsipu","created_at":"2018-12-12T21:12:09.574-08:00","display_name":"Tripti Gautam","url":"https://ggsipu.academia.edu/TriptiGautam","photo":"https://0.academia-photos.com/99080811/27084024/25503717/s65_tripti.gautam.jpg","has_photo":true,"department":{"id":39830,"name":"Computer Science","url":"https://ggsipu.academia.edu/Departments/Computer_Science/Documents","university":{"id":3880,"name":"Guru Gobind Singh Indraprastha University","url":"https://ggsipu.academia.edu/"}},"position":"Faculty Member","position_id":1,"interests":[{"id":284934,"name":"Google Maps API V3","url":"https://www.academia.edu/Documents/in/Google_Maps_API_V3"},{"id":84092,"name":"Web Technology","url":"https://www.academia.edu/Documents/in/Web_Technology"},{"id":42204,"name":"Engineering Chemistry","url":"https://www.academia.edu/Documents/in/Engineering_Chemistry"},{"id":636574,"name":"Sms Gateway","url":"https://www.academia.edu/Documents/in/Sms_Gateway"},{"id":81988,"name":"Comparative studies","url":"https://www.academia.edu/Documents/in/Comparative_studies"}]}</script><div class="work-card--no-attachment-details"><div style="font-weight: 700; font-size: 14px;">Abstract</div><div class="work-card--abstract js-swp-splash-abstract">Software metrics are a very important component in software development area. The most important challenge of any software developer is that ‘the software should be 100% accurate or with minimal defect’ when it reaches to the end-user. The earlier the defect is detected, the earlier the development cost also gets reduced. This is a fact that more complex the data or software, there is a more probability of the defect. So it is always desirable to use only the relevant and important data for the software development which will definitely reduce time and cost of the developer. The main objective of this paper is to find the important and relevant metrics in the software modules which will reduce the attribute in a data set. More the number of variables, more complex will be the system and more the defects; so it is always preferable to select the small feature set using feature selection and focus only on the important variable. The data set for the software bug prediction Chidamber and Kemerer metrics and Object Oriented metrics were taken from the Promise repository which is publicly available. The experiment from the 10 software modules (Jureczko M. Software Engineering: An International Journal 2011;1(1):95), ant, ivy, tomcat, berek, camel, jedit, lucene, poi, synapse and velocity, using feature selection techniques, Boruta, regsubset and FSelector, has shown that response for a class, lines of code and weighted methods for class are the most optimal metrics, whereas number of children and Depth of Inheritance Tree are least significant.</div></div><div class="request-upload--container"><p class="request-upload--title">Tripti Gautam hasn't uploaded this paper.</p><div class="request-upload--info-text"><svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="info-circle" class="request-upload--info-icon svg-inline--fa fa-info-circle fa-w-16" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M256 8C119.043 8 8 119.083 8 256c0 136.997 111.043 248 248 248s248-111.003 248-248C504 119.083 392.957 8 256 8zm0 110c23.196 0 42 18.804 42 42s-18.804 42-42 42-42-18.804-42-42 18.804-42 42-42zm56 254c0 6.627-5.373 12-12 12h-88c-6.627 0-12-5.373-12-12v-24c0-6.627 5.373-12 12-12h12v-64h-12c-6.627 0-12-5.373-12-12v-24c0-6.627 5.373-12 12-12h64c6.627 0 12 5.373 12 12v100h12c6.627 0 12 5.373 12 12v24z"></path></svg><p class="no-margin hide-on-small-mobile">Let Tripti know you want this paper to be uploaded.</p><p class="no-margin hide-above-small-mobile">Ask for this paper to be uploaded.</p></div><button class="work-cover--request-pdf-button small js-request-pdf-button hide-on-desktop"><svg style="width: 14px; 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