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Taxonomies in software engineering: A Systematic mapping study and a revised taxonomy development method
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0002-7220-9570
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0003-0639-4234
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering. Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
2017 (English)In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 85, p. 43-59Article in journal (Refereed) Published
Abstract [en]

Context: Software Engineering (SE) is an evolving discipline with new subareas being continuously developed and added. To structure and better understand the SE body of knowledge, taxonomies have been proposed in all SE knowledge areas. Objective: The objective of this paper is to characterize the state-of-the-art research on SE taxonomies. Method: A systematic mapping study was conducted, based on 270 primary studies. Results: An increasing number of SE taxonomies have been published since 2000 in a broad range of venues, including the top SE journals and conferences. The majority of taxonomies can be grouped into the following SWEBOI(knowledge areas: construction (19.55%), design (19.55%), requirements (15.50%) and maintenance (11.81%). Illustration (45.76%) is the most frequently used approach for taxonomy validation. Hierarchy (53.14%) and faceted analysis (39.48%) are the most frequently used classification structures. Most taxonomies rely on qualitative procedures to classify subject matter instances, but in most cases (86.53%) these procedures are not described in sufficient detail. The majority of the taxonomies (97%) target unique subject matters and many taxonomy-papers are cited frequently. Most SE taxonomies are designed in an ad-hoc way. To address this issue, we have revised an existing method for developing taxonomies in a more systematic way. Conclusion: There is a strong interest in taxonomies in SE, but few taxonomies are extended or revised. Taxonomy design decisions regarding the used classification structures, procedures and descriptive bases are usually not well described and motivated. (C) 2017 The Authors. Published by Elsevier B.V.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE BV , 2017. Vol. 85, p. 43-59
Keywords [en]
Taxonomy, Classification, Software engineering, Systematic mapping study
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-15161DOI: 10.1016/j.infsof.2017.01.006ISI: 000397553500003OAI: oai:DiVA.org:bth-15161DiVA, id: diva2:1143236
Available from: 2017-09-21 Created: 2017-09-21 Last updated: 2018-02-09Bibliographically approved
In thesis
1. Improving Expert Estimation of Software Development Effort in Agile Contexts
Open this publication in new window or tab >>Improving Expert Estimation of Software Development Effort in Agile Contexts
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2018
Series
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 4
Keywords
Expert effort estimation, Agile software development, Checklist
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-15870 (URN)978-91-7295-350-5 (ISBN)
Public defence
2018-03-20, J1650, BTH Campus Gräsvik, Karlskrona, 10:00 (English)
Opponent
Supervisors
Available from: 2018-02-15 Created: 2018-02-09 Last updated: 2018-04-09Bibliographically approved

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Usman, MuhammadBritto, RicardoBörstler, JürgenMendes, Emilia

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