Abstract:
This position paper argues that fault classification provides vital information for software analytics, and that machine learning techniques such as clustering can be app...Show MoreMetadata
Abstract:
This position paper argues that fault classification provides vital information for software analytics, and that machine learning techniques such as clustering can be applied to learn a project- (or organization-) specific fault taxonomy. Anecdotal evidence of this position is presented as well as possible areas of research for moving toward the posited goal.
Date of Conference: 02-02 March 2015
Date Added to IEEE Xplore: 02 April 2015
Electronic ISBN:978-1-4673-6923-7
Contents 