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Guidelines for the search strategy to update systematic literature reviews software engineering

机译:搜索策略准则更新系统文学评论软件工程

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Context: Systematic Literature Reviews (SLRs) have been adopted within Software Engineering (SE) for more than a decade to provide meaningful summaries of evidence on several topics. Many of these SLRs are now potentially not fully up-to-date, and there are no standard proposals on how to update SLRs in SE.Objective: The objective of this paper is to propose guidelines on how to best search for evidence when updating SLRs in SE, and to evaluate these guidelines using an SLR that was not employed during the formulation of the guidelines.Method: To propose our guidelines, we compare and discuss outcomes from applying different search strategies to identify primary studies in a published SLR, an SLR update, and two replications in the area of effort estimation. These guidelines are then evaluated using an SLR in the area of software ecosystems, its update and a replication.Results: The use of a single iteration forward snowballing with Google Scholar, and employing as a seed set the original SLR and its primary studies is the most cost-effective way to search for new evidence when updating SLRs. Furthermore, the importance of having more than one researcher involved in the selection of papers when applying the inclusion and exclusion criteria is highlighted through the results.Conclusions: Our proposed guidelines formulated based upon an effort estimation SLR, its update and two replications, were supported when using an SLR in the area of software ecosystems, its update and a replication. Therefore, we put forward that our guidelines ought to be adopted for updating SLRs in SE.
机译:背景信息:系统文献评论(SLRS)已在软件工程(SE)中采用十多年,以提供有关几个主题的有意义的证据摘要。这些SLR中的许多人现在可能不是完全最新的,并且如何在SE的方法中更新SLR的标准提案:本文的目标是提出如何在更新SLR时最佳地搜索证据的准则在SE中,并使用在制定指南期间没有采用的单反非雇用的SLR来评估这些指南。提出我们的指导方针,我们比较并讨论了应用不同的搜索战略,以确定发表的SLR中的初级研究,单反更新,以及努力估算领域的两种复制。然后使用软件生态系统的区域,更新和复制的区域进行评估这些指南。结果:使用单一迭代与谷歌学者的播放雪球,并雇用作为种子设置原始单反及其主要研究是最具成本效益的方式,用于在更新SLR时搜索新的证据。此外,通过结果突出了在申请包含和排斥标准时选择涉及文件的一名研究人员的重要性。结论:我们支持基于努力估算单反,其更新和两项重复制定的拟议指引。在软件生态系统区域中使用SLR时,其更新和复制。因此,我们提出了我们的准则,应该被采用更新SE中的SLR。

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