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Erschienen in:
2018 | OriginalPaper | Buchkapitel
104. Automating Search Strings for Secondary Studies
verfasst von : Francisco Carlos Souza, Alinne Santos, Stevão Andrade, Rafael Durelli, Vinicius Durelli, Rafael Oliveira
Erschienen in: Information Technology - New Generations
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Abstract
Background: secondary studies (SSs), in the form of systematic literature reviews and systematic mappings, have become a widely used evidence-based methodology to to create a classification scheme and structure research fields, thus giving an overview of what has been done in a given research field.
Problem: often, the conduction of high-quality SSs is hampered by the difficulties that stem from creating a proper “search string”. Creating sound search strings entails an array of skills and domain knowledge. Search strings are ill-defined because of a number of reasons. Two common reasons are (i) insuffient domain knowledge and (ii) time and resource constraints. When ill-defined search strings are used to carry out SSs, a potentially high number of pertinent studies is likely to be left out of the analysis.
Method: to overcome this limitation we propose an approach that applies a search-based algorithm called Hill Climbing to automate this key step in the conduction of SSs: search string generation and calibration.
Results: we conducted an experiment to evaluate our approach in terms of sensibility and precision. The results would seem to suggest that the precision and the sensibility our approach are 25.2% and 96.2%, respectively.
Conclusion: The results were promising given that our approach was able to generate and calibrate suitable search strings to support researchers during the conduction of SSs.