mpn.scorecard

mpn.scorecard is an R package designed to score other R packages on key attributes that help evaluate the risk of adding them to MPN. mpn.scorecard leans heavily on the metrics developed by R Validation Hub’s riskmetric R package, and has additional features related to the scoring and outputs. Each package is first evaluated based on code documentation, maintenance and sustainability, and transparency. Code coverage and R CMD Check results are then tabulated and saved out to a specified location. These metrics are summarized in a scorecard report.

Scoring a Package

You begin by scoring a package tarball, which will evaluate the aforementioned metrics, and save a json of the individual scores to out_dir. Code coverage and R CMD Check results are saved as RDS files to the same location.

results_dir <- score_pkg(
  pkg = "package_3.1.0.tar.gz",
  out_dir = file.path(tempdir(), "results")
)
#> rcmdcheck for package_3.1.0 passed

fs::dir_ls(results_dir)
#> /tmp/RtmpTFIt3N/results/package_3.1.0/package_3.1.0.check.rds
#> /tmp/RtmpTFIt3N/results/package_3.1.0/package_3.1.0.covr.rds
#> /tmp/RtmpTFIt3N/results/package_3.1.0/package_3.1.0.scorecard.json

Rendering a Scorecard

You can then render a scorecard PDF with the desired risk breaks, which determine the cutoff points for “Low”, “Medium”, and “High” risk. The R CMD Check output and tabulated code coverage will appear in the appendix of the report.

pdf_path <- render_scorecard(
  results_dir = results_dir,
  risk_breaks = c(0.3, 0.7)
)

browseURL(pdf_path)

Overall Scores

Each of the evaluated metrics is summarized at the top of the report:


Package Details

These metrics are further broken down in the next section, indicating specific risk assessments associated with the package:


Testing Results

Here you can see a summary of the R CMD Check and testing coverage results. These are weighted higher than the other metrics and will have a greater impact on the overall score. You can see the full results in the appendix.


Traceability Matrix (optional)

Our version of a traceability matrix maps R package exports to the following parameters:

  • R script the export is defined in
  • Any relevant documentation (man/ files)
  • Test files that call the export

You can generate a traceability matrix as a standalone object by not passing a results_dir:

trac_matrix <- make_traceability_matrix("package_3.1.0.tar.gz")

To add a traceability matrix to the scorecard, you must follow the steps below:

  • Score the package via score_pkg
  • Call make_traceability_matrix using the results_dir returned from score_pkg

If an RDS file matching the expected naming convention (<package_tarball_name>.export_doc.rds or package_3.1.0.export_doc.rds in the above example) is found in results_dir, the traceability matrix will be picked up and automatically included. Users can override this by setting add_traceability to FALSE.

results_dir <- score_pkg(
  pkg = "package_3.1.0.tar.gz",
  out_dir = file.path(tempdir(), "results")
)
#> rcmdcheck for package_3.1.0 passed

make_traceability_matrix("package_3.1.0.tar.gz", results_dir = results_dir)

fs::dir_ls(results_dir)
#> /tmp/RtmpTFIt3N/results/package_3.1.0/package_3.1.0.check.rds
#> /tmp/RtmpTFIt3N/results/package_3.1.0/package_3.1.0.covr.rds
#> /tmp/RtmpTFIt3N/results/package_3.1.0/package_3.1.0.export_doc.rds
#> /tmp/RtmpTFIt3N/results/package_3.1.0/package_3.1.0.scorecard.json

pdf_path <- render_scorecard(
  results_dir = results_dir,
  risk_breaks = c(0.3, 0.7),
  add_traceability = TRUE
)

browseURL(pdf_path)

Comments (optional)

Packages may optionally include a “Comments” text file for additional explanatory notes. Inclusion of this section works the same as a traceability matrix. If a comment file matching the expected naming convention (<package_tarball_name>.comments.txt or package_3.1.0.comments.txt in the above example) is found in results_dir, the section will be automatically be included.

Summary Report

If multiple packages have been scored, you can summarize each of the packages in a summary report using render_scorecard_summary, providing an easy way of summarizing the overall risk associated with each package:

pkg_tars <- c("package_3.1.0.tar.gz", "pkg1_2.0.4.tar.gz", "pkg2_1.6.3.tar.gz", "pkg3_0.3.0.tar.gz")
result_dirs <- purrr::map_chr(pkg_tars, ~ score_pkg(.x, out_dir))

pdf_sum_path <- render_scorecard_summary(result_dirs, snapshot = as.character(Sys.Date()))

browseURL(pdf_sum_path)

The report provides additional context, session info, proof points, etc., but will render a table that looks like the one below: