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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 [aut, cre], Laura Cunico [aut] |
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.pdf |
Vignettes: |
How to use oRus? References How does oRus Works? |
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 |
Please use the canonical form https://CRAN.R-project.org/package=oRus to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.