Search Strategy to Update Systematic Literature Reviews in Software Engineering

Search Strategy to Update Systematic Literature Reviews in Software Engineering. Mendes, E., Felizardo, K., Wohlin, C., & Kalinowski, M. In 45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019, Kallithea, Greece, Aug 28-30, pages 355-362, 2019. SEAA 2019 Best Paper Award!

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[Context] Systematic Literature Reviews (SLRs) have been adopted within the Software Engineering (SE) domain for more than a decade to provide meaningful summaries of evidence on several topics. Many of these SLRs are now outdated, and there are no standard proposals on how to update SLRs in SE. [Objective] The goal of this paper is to provide recommendations on how to best to search for evidence when updating SLRs in SE. [Method] To achieve our goal, we compare and discuss outcomes from applying different search strategies to identifying primary studies in a previously published SLR update on effort estimation. [Results] The use of a single iteration forward snowballing with Google Scholar, and employing the original SLR and its primary studies as a seed set seems to be the most cost-effective way to search for new evidence when updating SLRs. [Conclusions] The recommendations can be used to support decisions on how to update SLRs in SE.

@inproceedings{MendesFWK19,
  author    = {Emilia Mendes and Katia Felizardo and Claes Wohlin and Marcos Kalinowski},
  title     = {Search Strategy to Update Systematic Literature Reviews in Software Engineering},
  abstract  = {[Context] Systematic Literature Reviews (SLRs) have been adopted within the Software Engineering (SE) domain for more than a decade to provide meaningful summaries of evidence on several topics. Many of these SLRs are now outdated, and there are no standard proposals on how to update SLRs in SE. [Objective] The goal of this paper is to provide recommendations on how to best to search for  evidence when updating SLRs in SE. [Method] To achieve our goal, we compare and discuss outcomes from applying different search strategies to identifying primary studies in a previously published SLR update on effort estimation. [Results] The use of a single iteration forward snowballing with Google Scholar, and employing the original SLR and its primary studies as a seed set seems to be the most cost-effective way to search for new evidence when updating SLRs. [Conclusions] The recommendations can be used to support decisions on how to update SLRs in SE.},
  booktitle = {45th Euromicro Conference on Software Engineering and Advanced Applications, {SEAA} 2019, Kallithea, Greece, Aug 28-30},
  pages     = {355-362},
  note      = {<font color="red">SEAA 2019 Best Paper Award!</font>},          
  year      = {2019},
  urlAuthor_version       = {http://www.inf.puc-rio.br/~kalinowski/publications/MendesFWK19.pdf},
  doi       = {10.1109/SEAA.2019.00061},
}

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