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.

中文翻译：

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在软件工程中更新系统文献综述的搜索策略指南

语境

系统工程文献评论（SLR）已在软件工程（SE）中被采用，以提供有关多个主题的有意义的证据摘要。现在，许多此类SLR可能尚未完全更新，并且没有关于如何在SE中更新SLR的标准建议。

目的

本文的目的是提出有关在SE中更新SLR时如何最好地寻找证据的指南，并使用在制定指南期间未使用的SLR来评估这些指南。

方法

要提出我们的指南，我们将比较并讨论通过应用不同的搜索策略来识别已发布的SLR中的基础研究，SLR更新以及工作量估算领域中的两次重复得出的结果。然后，使用SLR在软件生态系统，其更新和复制领域中评估这些准则。

结果

与Google Scholar一起使用单迭代向前滚雪球，并使用原始SLR及其基础研究作为种子集，是在更新SLR时寻找新证据的最具成本效益的方法。此外，结果强调了在采用纳入和排除标准时，有不止一名研究人员参与论文选择的重要性。

结论

在软件生态系统，更新和复制领域中使用SLR时，将支持我们基于工作量估计SLR，其更新和两次复制制定的建议准则。因此，我们提出应该采用我们的准则来更新SE中的SLR。