Understanding Roxygen package documentation in R

Vidoni, Melina

doi:10.1016/j.jss.2022.111265

Search citation statements

Order By: Relevance

Paper Sections

Select...

Motivation and Significance1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2022

2024

Publication Types

Select...

Article3

Relationship

Self Cite1

Independent2

Authors

Journals

Cited by 3 publications

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nowadays, research on TD in scientific software and R programming is becoming popular [15,16,[18][19][20][21]. However, the availability of ASATs tools for R remains limited (Section 1.1).…”

Section: Motivation and Significancementioning

confidence: 99%

analyzeR: A SonarQube plugin for analyzing object-oriented R Packages

Chandramouli

Codabux²,

Vidoni³

2022

SoftwareX

Self Cite

View full text Add to dashboard Cite

Section: Motivation and Significancementioning

confidence: 99%

analyzeR: A SonarQube plugin for analyzing object-oriented R Packages

Chandramouli

Codabux²,

Vidoni³

2022

SoftwareX

Self Cite

View full text Add to dashboard Cite

Towards a taxonomy of Roxygen documentation in R packages

Vidoni

Codabux

2023

Empir Software Eng

View full text Add to dashboard Cite

Software documentation is often neglected, impacting maintenance and reuse and leading to technical issues. In particular, when working with scientific software, such issues in the documentation pose a risk to producing reliable scientific results as they may cause improper or incorrect use of the software. R is a popular programming language for scientific software with a prolific package-based ecosystem, where users contribute packages (i.e., libraries). R packages are intended to be reused, and their users rely extensively on the available documentation. Thus, understanding what information developers provide in their packages’ documentation (generally, through a system known as Roxygen, based on Javadoc) is essential to contribute to it. This study mined 379 GitHub repositories of R packages and analysed a sample to develop a taxonomy of natural language descriptions used in Roxygen documentation. This was done through hybrid card sorting, which included two experienced R developers. The resulting taxonomy covers parameters, returns, and descriptions, providing a baseline for further studies. Our taxonomy is the first of its kind for R. Based on previous studies in pure object-oriented languages, our taxonomy could be extensible to other dynamically-typed languages used in scientific programming.

show abstract

An exploratory study of software artifacts on GitHub from the lens of documentation

Venigalla,

Chimalakonda

2024

Information and Software Technology

View full text Add to dashboard Cite

Understanding Roxygen package documentation in R

Cited by 3 publications

References 11 publications

analyzeR: A SonarQube plugin for analyzing object-oriented R Packages

analyzeR: A SonarQube plugin for analyzing object-oriented R Packages

Towards a taxonomy of Roxygen documentation in R packages

An exploratory study of software artifacts on GitHub from the lens of documentation

Contact Info

Product

Resources

About