Using Forward Snowballing to update Systematic Reviews in Software Engineering. Felizardo, K., Mendes, E., Kalinowski, M., Souza, E., & Vijaykumar, N. 2016. cited By
Using Forward Snowballing to update Systematic Reviews in Software Engineering [link]Paper  doi  abstract   bibtex   
Background: A Systematic Literature Review (SLR) is a methodology used to aggregate relevant evidence related to one or more research questions. Whenever new evidence is published after the completion of a SLR, this SLR should be updated in order to preserve its value. However, updating SLRs involves significant effort. Objective: The goal of this paper is to investigate the application of forward snowballing to support the update of SLRs. Method: We compare outcomes of an update achieved using the forward snowballing versus a published update using the search-based approach, i.e., searching for studies in electronic databases using a search string. Results: Forward snowballing showed a higher precision and a slightly lower recall. It reduced in more than five times the number of primary studies to filter however missed one relevant study. Conclusions: Due to its high precision, we believe that the use of forward snowballing considerably reduces the effort in updating SLRs in Software Engineering; however the risk of missing relevant papers should not be underrated. © 2016 ACM.
@CONFERENCE{Felizardo2016,
author={Felizardo, K.R. and Mendes, E. and Kalinowski, M. and Souza, E.F. and Vijaykumar, N.L.},
title={Using Forward Snowballing to update Systematic Reviews in Software Engineering},
journal={International Symposium on Empirical Software Engineering and Measurement},
year={2016},
volume={08-09-September-2016},
doi={10.1145/2961111.2962630},
art_number={a53},
note={cited By },
url={https://doi.org/10.1145/2961111.2962630},
abstract={Background: A Systematic Literature Review (SLR) is a methodology used to aggregate relevant evidence related to one or more research questions. Whenever new evidence is published after the completion of a SLR, this SLR should be updated in order to preserve its value. However, updating SLRs involves significant effort. Objective: The goal of this paper is to investigate the application of forward snowballing to support the update of SLRs. Method: We compare outcomes of an update achieved using the forward snowballing versus a published update using the search-based approach, i.e., searching for studies in electronic databases using a search string. Results: Forward snowballing showed a higher precision and a slightly lower recall. It reduced in more than five times the number of primary studies to filter however missed one relevant study. Conclusions: Due to its high precision, we believe that the use of forward snowballing considerably reduces the effort in updating SLRs in Software Engineering; however the risk of missing relevant papers should not be underrated. © 2016 ACM.},
author_keywords={forward snowballing;  Systematic literature reviews},
keywords={Software engineering, Electronic database;  forward snowballing;  High-precision;  Research questions;  Search-based;  Systematic literature review;  Systematic literature review (SLR);  Systematic Review, Precision engineering},
publisher={IEEE Computer Society},
issn={19493770},
isbn={9781450344272},
document_type={Conference Paper},
source={Scopus},
}
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