A first implementation of automated parsing of user stories, when used to defined functional requirements for operational research mathematical models. It allows reading user stories, splitting them on the who-what-why template, and classifying them according to the parts of the mathematical model that they represent. Also provides semantic grouping of stories, for project management purposes.
| Version: | 1.0.0 | 
| Depends: | R (≥ 3.6.0) | 
| Imports: | dplyr, stringr, tm, tibble, tidytext, topicmodels, rmarkdown, xlsx, knitr | 
| Suggests: | reshape2, qpdf | 
| Published: | 2020-07-07 | 
| DOI: | 10.32614/CRAN.package.oRus | 
| Author: | Melina Vidoni | 
| Maintainer: | Melina Vidoni <melina.vidoni at rmit.edu.au> | 
| BugReports: | https://github.com/melvidoni/oRus/issues | 
| License: | GPL-3 | 
| URL: | https://github.com/melvidoni/oRus | 
| NeedsCompilation: | no | 
| Materials: | README, NEWS | 
| CRAN checks: | oRus results | 
| Reference manual: | oRus.html , oRus.pdf | 
| Vignettes: | How to use oRus? (source, R code) References (source, R code) How does oRus Works? (source, R code) | 
| Package source: | oRus_1.0.0.tar.gz | 
| Windows binaries: | r-devel: oRus_1.0.0.zip, r-release: oRus_1.0.0.zip, r-oldrel: oRus_1.0.0.zip | 
| macOS binaries: | r-release (arm64): oRus_1.0.0.tgz, r-oldrel (arm64): oRus_1.0.0.tgz, r-release (x86_64): oRus_1.0.0.tgz, r-oldrel (x86_64): oRus_1.0.0.tgz | 
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