Experience-based guidelines for effective and efficient data extraction in systematic reviews in software engineering

Vahid Garousi, Michael Felderer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)
111 Downloads (Pure)

Abstract

To systematically collect evidence and to structure a given area in software engineering (SE), Systematic Literature Reviews (SLR) and Systematic Mapping (SM) studies have become common. Data extraction is one of the main phases (activities) when conducting an SM or an SLR, whose objective is to extract required data from the primary studies and to accurately record the information researchers need to answer the questions of the SM/SLR study. Based on experience in a large number of SM/SLR studies, we and many other researchers have found the data extraction in SLRs to be time consuming and error-prone, thus raising the real need for heuristics and guidelines for effective and efficient data extraction in these studies, especially to be learnt by junior and young researchers. As a 'guideline' paper, this paper contributes a synthesized list of challenges usually faced during SLRs' data extraction phase and the corresponding solutions (guidelines). For our synthesis, we consider two data sources: (1) the pool of 16 SLR studies in which the authors have been involved in, as well as (2) a review of challenges and guidelines in the existing literature. Our experience in utilizing the presented guidelines in the near past have helped our junior colleagues to conduct data extractions more effectively and efficiently.

Original languageEnglish
Title of host publicationProceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering, EASE 2017
PublisherAssociation for Computing Machinery
Pages170-179
Number of pages10
VolumePart F128635
ISBN (Electronic)9781450348041
DOIs
Publication statusPublished - 15 Jun 2017
Externally publishedYes
Event21st International Conference on Evaluation and Assessment in Software Engineering, EASE 2017 - Karlskrona, Sweden
Duration: 15 Jun 201716 Jun 2017

Conference

Conference21st International Conference on Evaluation and Assessment in Software Engineering, EASE 2017
CountrySweden
CityKarlskrona
Period15/06/201716/06/2017

Keywords

  • Data extraction
  • Empirical software engineering
  • Research methodology
  • SLR
  • SM
  • Systematic literature reviews
  • Systematic mapping studies

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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