riskmetric
riskmetric
is a collection of risk metrics to evaluate the quality of R
packages.
This package is in experimentation. Final considerations about design are being considered, but core concepts are considered final.
Background
The risk of using an R package is evaluated based on a number of metrics meant to evaluate development best practices, code documentation, community engagement and development sustainability. We hope to provide a framework to quantify risk by assessing these metrics. This package serves as a starting point for exploring the heterogeneity of code quality, and begin a broader conversation about the validation of R packages. Primarily, this effort aims to provide some context for validation within regulated industries.
We separate three steps in the workflow to assess the risk of an R package using riskmetric
:
- Finding a source for package information (installed package or CRAN/git source)
pkg_ref()
- Assessing the package under validation criteria
pkg_assess()
- Scoring assessment criteria
pkg_score()
The results will be assembled in a dataset of validation criteria containing an overall risk score for each package as shown in the example below.
Installation
riskmetric
is not yet on CRAN. Until it is, install it using devtools
.
devtools::install_github("pharmaR/riskmetric")
Example
Scrape metadata locally or remotely, then assess that metadata and score it to estimate risk. For each package, derive a composite measure of risk, or a collection of individual scores which can be easily used to generate validation reports.
library(dplyr)
library(riskmetric)
pkg_ref(c("riskmetric", "utils", "tools")) %>%
pkg_assess() %>%
pkg_score()
Get Involved
We have a bi-weekly sprint meeting for developers to discuss the progress.
- Contact
yilong.zhang@merck.com
to be added to the meeting. - Date: 1st and 3rd Wednesday of the month.
- Meeting Time: 12:00PM - 12:30PM EST
- Project Planning Meeting Structure
- Milestone
- Meeting Room
riskmetric
is centrally a community project. Comfort with a quantification of
risk comes via consensus, and for that this project is dependent on close
community engagement. There are plenty of ways to help:
- Share the package
- File issues when you encounter bugs
- Weigh in on proposed metrics, or suggest a new one
- Help us devise the best way to summarize risk into a single score
- Help us keep documentation up to date
- Contribute code to tackle the metric backlog