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27861 On the pragmatic design of literature studies in software engineering: An experience-based guideline
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Kuhrmann, M. and Méndez Fernández, D. and Daneva, M. (2017) On the pragmatic design of literature studies in software engineering: An experience-based guideline. Journal of Empirical Software Engineering, 22 (1). pp. 1-40. ISSN 1382-3256 *** ISI Impact 1,393 ***

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Systematic literature studies have received much attention in empirical software engineering in recent years. They have become a powerful tool to collect and structure reported knowledge in a systematic and reproducible way. We distinguish systematic literature reviews to systematically analyze reported evidence in depth, and systematic mapping studies to structure a field of interest in a broader, usually quantified manner. Due to the rapidly increasing body of knowledge in software engineering, researchers who want to capture the published work in a domain often face an extensive amount of publications, which need to be screened, rated for relevance, classified, and eventually analyzed. Although there are several guidelines to conduct literature studies, they do not yet help researchers coping with the specific difficulties encountered in the practical application of these guidelines. In this article, we present an experience-based guideline to aid researchers in designing systematic literature studies with special emphasis on the data collection and selection procedures. Our guideline aims at providing a blueprint for a practical and pragmatic path through the plethora of currently available practices and deliverables capturing the dependencies among the single steps. The guideline emerges from various mapping studies and literature reviews conducted by the authors and provides recommendations for the general study design, data collection, and study selection procedures. Finally, we share our experiences and lessons learned in applying the different practices of the proposed guideline.

Item Type:Article
Research Group:EWI-SCS: Services, Cyber security and Safety
Research Program:CTIT-General
Research Project:EFFES: Effort estimation of business analytics services
Uncontrolled Keywords:evidence-based software engineering
ID Code:27861
Deposited On:03 April 2017
ISI Impact Factor:1,393
More Information:statistics

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