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What Evidence We Would Miss If We Do Not Use Grey Literature?

Published: 11 October 2021 Publication History

Abstract

Context: Multivocal Literature Reviews (MLR) search for evidence in both Traditional Literature (TL) and Grey Literature (GL). Despite the growing interest in MLR-based studies, the literature assessing how GL has contributed to MLR studies is still scarce. Objective: This research aims to assess how the use of GL contributed to MLR studies. By contributing, we mean, understanding to what extent GL is providing evidence that is indeed used by an MLR to answer its research question. Method: We start by conducting a tertiary study to identify MLR studies published between 2017 and 2019, selecting nine of them. We then identified the GL used in these studies and assessed to what extent the GLs are providing evidence that help these studies to answer their research questions. Results: Our analysis identified that 1) GL provided evidence not found in TL, 2) most of the GL sources were used to provide recommendations to solve problems, explain a topic, and classify the findings, and 3) 19 different GL types were used in the studies; these GLs were mainly produced by SE practitioners (including blog posts, slides presentations, or project descriptions). Conclusions: We evidence how GL contributed to MLR studies. We observed that if these GLs were not included in the MLR, several findings would have been omitted or weakened. We also described the challenges involved when conducting this investigation, along with potential ways to deal with them, which may help future SE researchers.

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        cover image ACM Conferences
        ESEM '21: Proceedings of the 15th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)
        October 2021
        368 pages
        ISBN:9781450386654
        DOI:10.1145/3475716
        © 2021 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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        Published: 11 October 2021

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        Author Tags

        1. Empirical Software Engineering
        2. GL
        3. Grey Literature
        4. MLR
        5. Multivocal Literature Review

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        • INES 2.0
        • FACEPE
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        Overall Acceptance Rate 130 of 594 submissions, 22%

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