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oRus: Operational Research User Stories

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 ORCID iD [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

Documentation:

Reference manual: oRus.pdf
Vignettes: How to use oRus?
References
How does oRus Works?

Downloads:

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

Linking:

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.
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