{"id":160994,"date":"2009-01-01T00:00:00","date_gmt":"2009-01-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/finding-dependencies-from-defect-history\/"},"modified":"2018-10-16T21:02:06","modified_gmt":"2018-10-17T04:02:06","slug":"finding-dependencies-from-defect-history","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/finding-dependencies-from-defect-history\/","title":{"rendered":"Finding Dependencies from Defect History"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Dependency analysis is an essential part of various software engineering activities like integration testing, reliability analysis and defect prediction. In this paper, we propose a new approach to identify dependencies between components and associate a notion of \u2015importance\u2016 with each dependency by mining the defect history of the system, which can be used to complement traditional dependency detection approaches like static analysis. By using our tool Ladybug that implements the approach, we have been able to identify important dependencies for Microsoft Windows Vista and Microsoft Windows Server 2008 and rank them for prioritizing testing especially when the number of dependent components was large. We have validated the accuracy of the results with domain experts who have worked on designing, implementing or maintaining the components involved.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Dependency analysis is an essential part of various software engineering activities like integration testing, reliability analysis and defect prediction. In this paper, we propose a new approach to identify dependencies between components and associate a notion of \u2015importance\u2016 with each dependency by mining the defect history of the system, which can be used to complement 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