Data for Applying Old Knowledge in Primary Study Selection
<p>Three data sets (Hall, Wahono, Danijel) generated from existing systematic literature review publications.</p> <p>Hall.csv is generated from Hall, et al., "A systematic literature review on fault prediction performance in software engineering", 2012.</p> <p>Wahono.csv is generated from Wahono, et al., "A systematic literature review of software defect prediction: research trends, datasets, methods and frameworks", 2015.</p> <p>Danijel.csv is generated from Radjenović, et al., "Software fault prediction metrics: A systematic literature review", 2013.</p> <p>Each data set has two subset, which are derived from the original set by publication years. E.g. Hall2007-.csv contains examples in Hall.csv published before and in 2007, while Hall2007+.csv contains examples published after 2007.</p> <p>These data sets are used in our the newly submitted paper: "Testing Reading Tactics for Automated Reading Assistance: Is it Useful to Apply Old Knowledge?".</p>
ShareScore
40/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 0
Topics
Dataset details
- Repository
- zenodo
- Published
- February 12, 2017
- License
- cc-by-4.0
- DOI
- 10.5281/zenodo.290670
Scored with release 0.9.0
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