{"id":140148,"date":"2020-01-24T12:14:44","date_gmt":"2020-01-24T17:14:44","guid":{"rendered":"https:\/\/www.immortalitymedicine.tv\/jenkins-creator-launches-startup-to-speed-software-testing-with-machine-learning-adtmag-adt-magazine\/"},"modified":"2024-08-18T11:34:25","modified_gmt":"2024-08-18T15:34:25","slug":"jenkins-creator-launches-startup-to-speed-software-testing-with-machine-learning-adtmag-adt-magazine","status":"publish","type":"post","link":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/machine-learning\/jenkins-creator-launches-startup-to-speed-software-testing-with-machine-learning-adtmag-adt-magazine.php","title":{"rendered":"Jenkins Creator Launches Startup To Speed Software Testing with Machine Learning &#8212; ADTmag &#8211; ADT Magazine"},"content":{"rendered":"<p><p>Jenkins Creator Launches Startup To Speed Software Testing with Machine Learning <\/p>\n<p>Kohsuke Kawaguchi, creator of  the open source Jenkins continuous integration\/continuous delivery (CI\/CD)  server, and Harpreet Singh, former head of the product group at Atlassian, have  launched a startup that's using machine learning (ML) to speed up the software  testing process. <\/p>\n<p>Their new company, Launchable, which emerged  from stealth mode on Thursday, is developing a software-as-a-service (SaaS) product with  the ability to predict the likelihood of a failure for each test case, given a  change in the source code. The service will use ML to extract insights from the  massive and growing amount of data generated by the increasingly automated software  development process to make its predictions. <\/p>\n<p>\"As a developer, I've  seen this problem of slow feedback from tests first-hand,\" Kawaguchi told ADTmag.  \"And as the guy who drove automation in the industry with Jenkins, it  seemed to me that we could make use of all that data the automation is  generating by applying machine learning to the problem. I thought we should be  able to train the machine on the model and apply quantifiable metrics, instead  of relying on human experience and gut instinct. We believe we can predict,  with meaningful accuracy, what tests are more likely to catch a regression,  given what has changed, and that translates to faster feedback to developers.\" <\/p>\n<p>The strategy here is to run  only a meaningful subset of tests, in the order that minimizes the feedback  delay.<\/p>\n<p>Kawaguchi (known as \"KK\")  and Singh worked together at CloudBees, the chief commercial supporter of Jenkins. Singh left that company in 2018 to serve as GM of  Atlassian's Bitbucket cloud group. Kawaguchi became an elite  developer and architect at CloudBees, and he's been a part of the community  throughout the evolution of this technology. His departure from the company was amicable: Its CEO and co-founder  Sacha Labourey is an investor in the startup, and Kawaguchi will continue to be  involved with the Jenkins community, he said. <\/p>\n<p>Software testing has been a  passion of Kawaguchi's since his days at Sun Microsystems, where he developed  Jenkins as a fork of the Hudson CI server in 2011. Singh also worked at Sun and  served as the first product manager for Hudson before working on Jenkins. They  will serve as co-CEOs of the new company. They reportedly snagged $3.2 million  in seed funding to get the ball rolling. <\/p>\n<p>\"KK and I got to talking  about how the way we test now impacts developer productivity, and how machine  learning could be used to address the problem,\" Singh said. \"And then  we started talking about doing a startup. We sat next to each other at  CloudBees for eight years; it was an opportunity I couldn't pass up.\"<\/p>\n<p>An ML engine is at the heart  of the Launchable SaaS, but it's really all about the data, Singh said.<\/p>\n<p>\"We saw all these sales  and marketing guys making data-driven decisions -- even more than the engineers,  which was kind of embarrassing,\" Singh said. \"So it became a mission  for us to change that. It's kind of our north star.\"<\/p>\n<p>The co-execs are currently  talking with potential partners and recruiting engineers and data scientists.  They offered no hard release date, but they said they expect a version of the  Launchable SaaS to become generally available later this year. <\/p>\n<p>Posted by John K. Waters on 01\/23\/2020 at 8:41 AM<\/p>\n<p><!-- Auto Generated --><\/p>\n<p>Read more from the original source:<br \/>\n<a target=\"_blank\" href=\"https:\/\/adtmag.com\/blogs\/watersworks\/2020\/01\/jenkins-creator-software-testing-machine-learning.aspx\" title=\"Jenkins Creator Launches Startup To Speed Software Testing with Machine Learning -- ADTmag - ADT Magazine\" rel=\"noopener noreferrer\">Jenkins Creator Launches Startup To Speed Software Testing with Machine Learning -- ADTmag - ADT Magazine<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p> Jenkins Creator Launches Startup To Speed Software Testing with Machine Learning Kohsuke Kawaguchi, creator of the open source Jenkins continuous integration\/continuous delivery (CI\/CD) server, and Harpreet Singh, former head of the product group at Atlassian, have launched a startup that's using machine learning (ML) to speed up the software testing process. Their new company, Launchable, which emerged from stealth mode on Thursday, is developing a software-as-a-service (SaaS) product with the ability to predict the likelihood of a failure for each test case, given a change in the source code. The service will use ML to extract insights from the massive and growing amount of data generated by the increasingly automated software development process to make its predictions <a href=\"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/machine-learning\/jenkins-creator-launches-startup-to-speed-software-testing-with-machine-learning-adtmag-adt-magazine.php\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":65,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"limit_modified_date":"","last_modified_date":"","_lmt_disableupdate":"","_lmt_disable":"","footnotes":""},"categories":[1231415],"tags":[],"class_list":["post-140148","post","type-post","status-publish","format-standard","hentry","category-machine-learning"],"modified_by":null,"_links":{"self":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/140148"}],"collection":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/users\/65"}],"replies":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/comments?post=140148"}],"version-history":[{"count":0,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/140148\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/media?parent=140148"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/categories?post=140148"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/tags?post=140148"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}