Do information retrieval algorithms for automated traceability perform effectively on issue tracking system data?

• Verfasst von: Merten, Thorsten [VerfasserIn]
• Verfasst von: Paech, Barbara [VerfasserIn]
• Titel: Do information retrieval algorithms for automated traceability perform effectively on issue tracking system data?
• Verf.angabe: Thorsten Merten, Daniel Krämer, Bastian Mager, Paul Schell, Simone Bürsner, and Barbara Paech
• Umfang: 18 S.
• Fussnoten: Gesehen am 16.08.2018
• Titel Quelle: Enthalten in: Requirements Engineering: Foundation for Software Quality
• Jahr Quelle: 2016
• Band/Heft Quelle: (2016), S. 45-62
• ISBN Quelle: 978-3-319-30282-9
• DOI: doi:10.1007/978-3-319-30282-9_4
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1580109993

Abstract

Traces between issues in issue tracking systems connect bug reports to software features, they connect competing implementation ideas for a software feature or they identify duplicate issues. However, the trace quality is usually very low. To improve the trace quality between requirements, features, and bugs, information retrieval algorithms for automated trace retrieval can be employed. Prevailing research focusses on structured and well-formed documents, such as natural language requirement descriptions. In contrast, the information in issue tracking systems is often poorly structured and contains digressing discussions or noise, such as code snippets, stack traces, and links.