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Comparing Methods to Identify Defect Reports in a Change Management Database
AT and T Labs - Research, USA.ORCID iD: 0000-0002-1660-199X
AT and T Labs - Research, USA.
2008 (English)In: DEFECTS'08: 2008 International Symposium on Software Testing and Analysis - Proceedings of the 2008 Workshop on Defects in Large Software Systems 2008, DEFECTS'08, 2008, p. 27-31Conference paper, Published paper (Refereed)
Abstract [en]

A key problem when doing automated fault analysis and fault prediction from information in a software change management database is how to determine which change reports represent software faults. In some change management systems, there is no simple way to distinguish fault reports from changes made to add new functionality or perform routine maintenance. This paper describes a comparison of two methods for classifying change reports for a large software system, and concludes that, for that particular system, the stage of development when the report was initialized is a more accurate indicator of its fault status than the presence of certain keywords in the report's natural language description.

Place, publisher, year, edition, pages
2008. p. 27-31
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-23702DOI: 10.1145/1390817.1390825Scopus ID: 2-s2.0-57349125839ISBN: 9781605580517 (print)OAI: oai:DiVA.org:mdh-23702DiVA, id: diva2:680462
Conference
2008 Workshop on Defects in Large Software Systems 2008, DEFECTS'08; Seattle, WA; United States; 20 July 2008 through 20 July 2008
Available from: 2013-12-18 Created: 2013-12-18 Last updated: 2017-03-06Bibliographically approved

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Weyuker, Elaine

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