DocumentCode :
555372
Title :
A combination approach for enhancing automated traceability: (NIER track)
Author :
Chen, Xiaofan ; Hosking, John ; Grundy, John
Author_Institution :
Dept. of Comput. Sci., Univ. of Auckland, Auckland, New Zealand
fYear :
2011
fDate :
21-28 May 2011
Firstpage :
912
Lastpage :
915
Abstract :
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.
Keywords :
information retrieval; program diagnostics; software engineering; automated traceability system; document clustering; information retrieval; key phrases; regular expression; traceability link recovery; Clustering algorithms; Documentation; Information retrieval; Large scale integration; Software; Thesauri; Unified modeling language; clustering; key phrases; regular expression; traceability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering (ICSE), 2011 33rd International Conference on
Conference_Location :
Honolulu, HI
ISSN :
0270-5257
Print_ISBN :
978-1-4503-0445-0
Electronic_ISBN :
0270-5257
Type :
conf
DOI :
10.1145/1985793.1985943
Filename :
6032550
Link To Document :
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