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Introduction to the Special Issue on: Grey Literature and Multivocal Literature Reviews (MLRs) in software engineering
Queen's University Belfast, GBR.
Queen's University Belfast, GBR.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0003-3818-4442
University of Oulu, FIN.
2022 (English)In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 141, article id 106697Article in journal, Editorial material (Refereed) Published
Abstract [en]

In parallel to academic (peer-reviewed) literature (e.g., journal and conference papers), an enormous extent of grey literature (GL) has accumulated since the inception of software engineering (SE). GL is often defined as “literature that is not formally published in sources such as books or journal articles”, e.g., in the form of trade magazines, online blog-posts, technical reports, and online videos such as tutorial and presentation videos. GL is typically produced by SE practitioners. We have observed that researchers are increasingly using and benefitting from the knowledge available within GL. Related to the notion of GL is the notion of Multivocal Literature Reviews (MLRs) in SE, i.e., a MLR is a form of a Systematic Literature Review (SLR) which includes knowledge and/or evidence from the GL in addition to the peer-reviewed literature. MLRs are useful for both researchers and practitioners because they provide summaries of both the state-of-the-art and -practice in a given area. MLRs are popular in other fields and have started to appear in SE community. It is timely then for a Special Issue (SI) focusing on GL and MLRs in SE. From the pool of 13 submitted papers, and after following a rigorous peer review process, seven papers were accepted for this SI. In this introduction we provide a brief overview of GL and MLRs in SE, and then a brief summary of the seven papers published in this SI. © 2021

Place, publisher, year, edition, pages
Elsevier B.V. , 2022. Vol. 141, article id 106697
Keywords [en]
Epistemology, Evidence-based software engineering, Grey literature, Multivocal literature review
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-22049DOI: 10.1016/j.infsof.2021.106697ISI: 000701988700001OAI: oai:DiVA.org:bth-22049DiVA, id: diva2:1588375
Available from: 2021-08-27 Created: 2021-08-27 Last updated: 2021-10-15Bibliographically approved

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Felderer, Michael

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