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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 VidoniORCID 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.html ,oRus.pdf
Vignettes:How to use oRus? (source,R code)
References (source,R code)
How does oRus Works? (source,R code)

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:

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