{"id":160095,"date":"2010-11-01T00:00:00","date_gmt":"2010-11-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/change-bursts-as-defect-predictors\/"},"modified":"2018-10-16T20:08:28","modified_gmt":"2018-10-17T03:08:28","slug":"change-bursts-as-defect-predictors","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/change-bursts-as-defect-predictors\/","title":{"rendered":"Change Bursts as Defect Predictors"},"content":{"rendered":"<div class=\"asset-content\">\n<p>In software development, every change induces a risk. What happens if code changes again and again in some period of time? In an empirical study on Windows Vista, we found that the features of such change bursts have the highest predictive power for defect-prone components. With precision and recall values well above 90%, change bursts significantly improve upon earlier predictors such as complexity metrics, code churn, or organizational structure. As they only rely on version history and a controlled change process, change bursts are straight-forward to detect and deploy.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In software development, every change induces a risk. What happens if code changes again and again in some period of time? In an empirical study on Windows Vista, we found that the features of such change bursts have the highest predictive power for defect-prone components. With precision and recall values well above 90%, change bursts [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"IEEE","msr_publisher_other":"","msr_booktitle":"Proceedings of the 21st IEEE International Symposium on Software Reliability Engineering (ISSRE)","msr_chapter":"","msr_edition":"Proceedings of the 21st IEEE International Symposium on Software Reliability Engineering (ISSRE)","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"\u00a9 2010 IEEE. Personal use of this material is permitted. However, permission to reprint\/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.http:\/\/www.ieee.org\/","msr_conference_name":"Proceedings of the 21st IEEE International Symposium on Software Reliability Engineering (ISSRE)","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"Nachiappan Nagappan, Andreas Zeller, Thomas 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