{"id":322,"date":"2018-08-15T18:32:10","date_gmt":"2018-08-15T18:32:10","guid":{"rendered":"http:\/\/metrics.blogg.gu.se\/?p=322"},"modified":"2018-08-15T18:32:10","modified_gmt":"2018-08-15T18:32:10","slug":"software-analytics-the-next-thing-for-software-metrics-in-modern-companies","status":"publish","type":"post","link":"https:\/\/metrics.blogg.gu.se\/?p=322","title":{"rendered":"Software analytics, the next thing for software metrics in modern companies"},"content":{"rendered":"<p>The hot summer in Europe provided a lot of time for relaxation and contemplation:) I&#8217;ve spent some of the warm days reading some articles for the upcoming SEAA session on software analytics, which is a follow up of the special issue of IST:\u00a0<a href=\"https:\/\/doi.org\/10.1016\/j.infsof.2018.03.001\">https:\/\/doi.org\/10.1016\/j.infsof.2018.03.001\u00a0<\/a><\/p>\n<p>Software analytics, simply put, is using data and its visualisation to make decisions about software development. The typical data sources, both in literature and observed in many companies, are:<\/p>\n<ol>\n<li>Source code measurements from Git<\/li>\n<li>Defect data from JIRA<\/li>\n<li>Requirements data<\/li>\n<li>Customer data, a.k.a. field data<\/li>\n<li>Performance\/profiling data from running the system<\/li>\n<li>Process data from time reporting systems, Windows journals, etc.<\/li>\n<\/ol>\n<p>These data sources allow us to find bottlenecks in the performance of our software and the performance of our progress.<\/p>\n<p>Software analytics has been in the heart of such paradigms as the MVP from The Lean Start-Up, where they provide the ability to steer which features are developed and which are abandoned.<\/p>\n<p>Our experiences from Software Analytics are described in the book\u00a0<em>Software Development Measurement Programs, chapter 5:\u00a0<\/em><a href=\"https:\/\/www.springer.com\/us\/book\/9783319918358\">https:\/\/www.springer.com\/us\/book\/9783319918358\u00a0<\/a><\/p>\n<p>&nbsp;<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter  wp-image-323\" src=\"http:\/\/metrics.blogg.gu.se\/files\/2018\/08\/cover_software_development_measurement_programs.jpg\" alt=\"\" width=\"226\" height=\"351\" srcset=\"https:\/\/metrics.blogg.gu.se\/files\/2018\/08\/cover_software_development_measurement_programs.jpg 916w, https:\/\/metrics.blogg.gu.se\/files\/2018\/08\/cover_software_development_measurement_programs-193x300.jpg 193w, https:\/\/metrics.blogg.gu.se\/files\/2018\/08\/cover_software_development_measurement_programs-768x1194.jpg 768w, https:\/\/metrics.blogg.gu.se\/files\/2018\/08\/cover_software_development_measurement_programs-659x1024.jpg 659w\" sizes=\"(max-width: 226px) 85vw, 226px\" \/><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The hot summer in Europe provided a lot of time for relaxation and contemplation:) I&#8217;ve spent some of the warm days reading some articles for the upcoming SEAA session on software analytics, which is a follow up of the special issue of IST:\u00a0https:\/\/doi.org\/10.1016\/j.infsof.2018.03.001\u00a0 Software analytics, simply put, is using data and its visualisation to make &hellip; <a href=\"https:\/\/metrics.blogg.gu.se\/?p=322\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Software analytics, the next thing for software metrics in modern companies&#8221;<\/span><\/a><\/p>\n","protected":false},"author":68,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"_links":{"self":[{"href":"https:\/\/metrics.blogg.gu.se\/index.php?rest_route=\/wp\/v2\/posts\/322"}],"collection":[{"href":"https:\/\/metrics.blogg.gu.se\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/metrics.blogg.gu.se\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/metrics.blogg.gu.se\/index.php?rest_route=\/wp\/v2\/users\/68"}],"replies":[{"embeddable":true,"href":"https:\/\/metrics.blogg.gu.se\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=322"}],"version-history":[{"count":1,"href":"https:\/\/metrics.blogg.gu.se\/index.php?rest_route=\/wp\/v2\/posts\/322\/revisions"}],"predecessor-version":[{"id":324,"href":"https:\/\/metrics.blogg.gu.se\/index.php?rest_route=\/wp\/v2\/posts\/322\/revisions\/324"}],"wp:attachment":[{"href":"https:\/\/metrics.blogg.gu.se\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=322"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/metrics.blogg.gu.se\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=322"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/metrics.blogg.gu.se\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=322"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}