A combination approach for enhancing automated traceability (NIER track)

Xiaofan Chen, John Hosking, John Grundy

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

7 Citations (Scopus)


Tracking a variety of traceability links between artifacts assists software developers in comprehension, efficient development, and effective management of a system. Traceability systems to date based on various Information Retrieval (IR) techniques have been faced with a major open research challenge: how to extract these links with both high precision and high recall. In this paper we describe an experimental approach that combines Regular Expression, Key Phrases, and Clustering with IR techniques to enhance the performance of IR for traceability link recovery between documents and source code. Our preliminary experimental results show that our combination technique improves the performance of IR, increases the precision of retrieved links, and recovers more true links than IR alone.

Original languageEnglish
Title of host publicationICSE 2011 - 33rd International Conference on Software Engineering, Proceedings of the Conference
Number of pages4
Publication statusPublished - 2011
Externally publishedYes
EventInternational Conference on Software Engineering 2011 - The Hilton Hawaiian Village Beach Resort and Spa, Waikiki, Honolulu, United States of America
Duration: 21 May 201128 May 2011
Conference number: 33rd
https://ieeexplore.ieee.org/xpl/conhome/6032121/proceeding (Proceedings)


ConferenceInternational Conference on Software Engineering 2011
Abbreviated titleICSE 2011
Country/TerritoryUnited States of America
CityWaikiki, Honolulu
Internet address


  • clustering
  • key phrases
  • regular expression
  • traceability

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