DocumentCode
3029202
Title
Towards evidence-based ontology for supporting Systematic Literature Review
Author
Yueming Sun ; Ye Yang ; He Zhang ; Wen Zhang ; Qing Wang
Author_Institution
Lab. for Internet Software Technol., Inst. of Software, Beijing, China
fYear
2012
fDate
14-15 May 2012
Firstpage
171
Lastpage
175
Abstract
Systematic Literature Review (SLR) has become an important software engineering research method but costs tremendous efforts. This paper proposes an approach to leverage on empirically evolved ontology to support automating key SLR activities. [Method]: First, we propose an ontology, SLRONT, built on SLR experiences and best practices as a groundwork to capture common terminologies and their relationships during SLR processes; second, we present an extended version of SLRONT, the COSONT and instantiate it with the knowledge and concepts extracted from structured abstracts. Case studies illustrate the details of applying it for supporting SLR steps. Results show that through using COSONT, we acquire the same conclusion compared with sheer manual works, but the efforts involved is significantly reduced. The approach of using ontology could effectively and efficiently support the conducting of systematic literature review.
Keywords
case-based reasoning; knowledge acquisition; ontologies (artificial intelligence); software engineering; COSONT; SLR process; concept extraction; evidence-based ontology; extended SLRONT version; knowledge extraction; software engineering research method; structured abstracts; systematic literature review; ontology; software cost estimation; structured abstract; systematic literature review;
fLanguage
English
Publisher
iet
Conference_Titel
Evaluation & Assessment in Software Engineering (EASE 2012), 16th International Conference on
Conference_Location
Ciudad Real
Electronic_ISBN
978-1-84919-541-6
Type
conf
DOI
10.1049/ic.2012.0022
Filename
6272511
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