{"id":7990,"date":"2025-04-09T11:27:09","date_gmt":"2025-04-09T11:27:09","guid":{"rendered":"https:\/\/scai.kibu.ac.ke\/?p=7990"},"modified":"2025-12-24T00:38:50","modified_gmt":"2025-12-24T00:38:50","slug":"performance-and-cost-effectiveness-of-change-burst-metrics-in-predicting-software-faults","status":"publish","type":"post","link":"https:\/\/kibu.ac.ke\/scai\/performance-and-cost-effectiveness-of-change-burst-metrics-in-predicting-software-faults\/","title":{"rendered":"Performance and cost-effectiveness of change burst metrics in predicting software faults"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"7990\" class=\"elementor elementor-7990\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-60289c66 elementor-section-full_width elementor-section-height-min-height elementor-section-items-stretch elementor-section-height-default\" data-id=\"60289c66\" data-element_type=\"section\" id=\"ourgoal\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-122ccea1\" data-id=\"122ccea1\" data-element_type=\"column\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-22eac6e elementor-widget elementor-widget-theme-post-title elementor-page-title elementor-widget-heading\" data-id=\"22eac6e\" data-element_type=\"widget\" data-widget_type=\"theme-post-title.default\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">Performance and cost-effectiveness of change burst metrics in predicting software faults<\/h1>\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-5172e37d elementor-section-height-min-height elementor-section-boxed elementor-section-height-default elementor-section-items-middle\" data-id=\"5172e37d\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-562239c8\" data-id=\"562239c8\" data-element_type=\"column\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-1c31b472 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1c31b472\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-inner-column elementor-element elementor-element-16a3f1a2 elementor-invisible\" data-id=\"16a3f1a2\" data-element_type=\"column\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;animation&quot;:&quot;fadeIn&quot;,&quot;animation_mobile&quot;:&quot;none&quot;}\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-2cf41669 elementor-widget__width-auto elementor-widget elementor-widget-heading\" data-id=\"2cf41669\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">2019<\/h2>\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-inner-column elementor-element elementor-element-32b28434 elementor-invisible\" data-id=\"32b28434\" data-element_type=\"column\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;animation&quot;:&quot;fadeIn&quot;,&quot;animation_mobile&quot;:&quot;none&quot;}\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-785d5d13 elementor-widget elementor-widget-heading\" data-id=\"785d5d13\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">KIBU Authors<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2d06e5d8 elementor-invisible elementor-widget elementor-widget-text-editor\" data-id=\"2d06e5d8\" data-element_type=\"widget\" data-settings=\"{&quot;_animation&quot;:&quot;fadeIn&quot;}\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>Franklin Wabwoba<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-inner-column elementor-element elementor-element-1ccfad34 elementor-invisible\" data-id=\"1ccfad34\" data-element_type=\"column\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;animation&quot;:&quot;fadeIn&quot;,&quot;animation_mobile&quot;:&quot;none&quot;}\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-35796191 elementor-tablet-align-left elementor-invisible elementor-widget elementor-widget-button\" data-id=\"35796191\" data-element_type=\"widget\" data-settings=\"{&quot;_animation&quot;:&quot;fadeInLeft&quot;}\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-shrink\" href=\"https:\/\/link.springer.com\/article\/10.1007\/s10115-018-1241-7\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">VIEW ON PUBLISHER SITE<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-25ccf292 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"25ccf292\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-inner-column elementor-element elementor-element-7611af44 elementor-invisible\" data-id=\"7611af44\" data-element_type=\"column\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;animation&quot;:&quot;fadeIn&quot;,&quot;animation_mobile&quot;:&quot;none&quot;}\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-f8a8518 elementor-widget elementor-widget-heading\" data-id=\"f8a8518\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-52fcf571 elementor-invisible elementor-widget elementor-widget-text-editor\" data-id=\"52fcf571\" data-element_type=\"widget\" data-settings=\"{&quot;_animation&quot;:&quot;fadeIn&quot;}\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>The purpose of this study is to determine a type of software metric at file level exhibiting the best prediction performance. Studies have shown that software process metrics are better predictors of software faults than software product metrics. However, there is need for a specific software process metric which can guarantee the best fault prediction performances consistently across different experimental contexts. We collected software metrics data from Open Source Software projects. We used logistic regression and linear regression algorithms to predict bug status and number of bugs corresponding to a file, respectively. The prediction performance of these models was evaluated against numerical and graphical prediction model performance measures. We found that change burst metrics exhibit the best numerical performance measures and have the highest fault detection probability and least cost of misclassification of software components.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>2019 KIBU Authors Franklin Wabwoba VIEW ON PUBLISHER SITE Abstract The purpose of this study is to determine a type of software metric at file level exhibiting the best prediction performance. Studies have shown that software process metrics are better predictors of software faults than software product metrics. However, there is need for a specific [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_header_footer","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[],"class_list":["post-7990","post","type-post","status-publish","format-standard","hentry","category-research-list"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Performance and cost-effectiveness of change burst metrics in predicting software faults - School of Computing &amp; Informatics<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/kibu.ac.ke\/scai\/performance-and-cost-effectiveness-of-change-burst-metrics-in-predicting-software-faults\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Performance and cost-effectiveness of change burst metrics in predicting software faults - School of Computing &amp; Informatics\" \/>\n<meta property=\"og:description\" content=\"2019 KIBU Authors Franklin Wabwoba VIEW ON PUBLISHER SITE Abstract The purpose of this study is to determine a type of software metric at file level exhibiting the best prediction performance. Studies have shown that software process metrics are better predictors of software faults than software product metrics. However, there is need for a specific [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/kibu.ac.ke\/scai\/performance-and-cost-effectiveness-of-change-burst-metrics-in-predicting-software-faults\/\" \/>\n<meta property=\"og:site_name\" content=\"School of Computing &amp; Informatics\" \/>\n<meta property=\"article:published_time\" content=\"2025-04-09T11:27:09+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-12-24T00:38:50+00:00\" \/>\n<meta name=\"author\" content=\"kibabii\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"kibabii\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/kibu.ac.ke\/scai\/performance-and-cost-effectiveness-of-change-burst-metrics-in-predicting-software-faults\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/kibu.ac.ke\/scai\/performance-and-cost-effectiveness-of-change-burst-metrics-in-predicting-software-faults\/\"},\"author\":{\"name\":\"kibabii\",\"@id\":\"https:\/\/kibu.ac.ke\/scai\/#\/schema\/person\/f24ef483cba6d32518303e5d7f89741d\"},\"headline\":\"Performance and cost-effectiveness of change burst metrics in predicting software faults\",\"datePublished\":\"2025-04-09T11:27:09+00:00\",\"dateModified\":\"2025-12-24T00:38:50+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/kibu.ac.ke\/scai\/performance-and-cost-effectiveness-of-change-burst-metrics-in-predicting-software-faults\/\"},\"wordCount\":155,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/kibu.ac.ke\/scai\/#organization\"},\"articleSection\":[\"Research List\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/kibu.ac.ke\/scai\/performance-and-cost-effectiveness-of-change-burst-metrics-in-predicting-software-faults\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/kibu.ac.ke\/scai\/performance-and-cost-effectiveness-of-change-burst-metrics-in-predicting-software-faults\/\",\"url\":\"https:\/\/kibu.ac.ke\/scai\/performance-and-cost-effectiveness-of-change-burst-metrics-in-predicting-software-faults\/\",\"name\":\"Performance and cost-effectiveness of change burst metrics in predicting software faults - School of Computing &amp; 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