devarops/mutant

mutation testing for R

mutant

mutant - mutation testing

(wikipedia: mutation testing vs. fuzzing)

info

• mutaters: in mutaters.R
  • currently only have:
    • boolean replacement (TRUE -> FALSE, and vice versa)
    • binary operator replacement (e.g., > to >=)

install

remotes::install_github("ropenscilabs/astr", "roepnsci/mutant")

current workflow

As of this writing (2020-05-18) ...

# path to an R package with working tests in tests/
path <- "../randgeo/" 
## collect fxns into an environment
env <- collect_fxns(path)
ls.str(env)
## make pkg map for later
pkgmap <- make_pkg_map(path)
## parse fxns with getParseData
# fxns <- parse_fxns(env)
## mutate something
mut_fxns <- mutate(as.list(env))
# what fxn was mutated?
which(vapply(mut_fxns, function(x) attr(x, "mutated"), logical(1)))
## write a new package with test suite to a tempdir
new_fxns <- make_fxns(mut_fxns)
newpath <- write_mutated_pkg(pkg_path = path, fxns = new_fxns, map = pkgmap)
## run test suite & collect diagnostics
mutout <- mutation_test(newpath)
# mutout
dplyr::select(data.frame(mutout), file, context, test, nb, failed, skipped, error, warning, passed)

This will all be internal code however - only exposing probably a few functions to users to run mutation testing, do something with results, etc.

To do

brainstorming high level steps:

1. map input package api
   • optionally map what test lines are linked to what code lines (#10)
2. generate mutants
   • each of these are full packages, which with a different mutation
3. put all mutants in a queue (#2)
4. test all mutants - pull jobs from the queue until all are done
5. collate results, write to disk

Meta

• Please report any issues or bugs.
• License: MIT
• Get citation information for mutant in R doing citation(package = 'mutant')
• Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.