This repository contains an R package for "Directed Random" research paper. The devtools
development framework was used to implement this R package. The content of this repository are the following:
The following instructions will get you a copy of the project up and running on your local R environment. This method is ideal if you plan to leverage, without modification, our existing functions and data sets.
Please note that these instructions have been tested on an Ubuntu 16.04 LTS workstation running the following version of R:
R version 3.3.3 (2017-03-06) -- "Another Canoe"
Copyright (C) 2017 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
You would need devtools
to install our package:
You can type the next command in your R development environment if you want to install this package:
devtools::install_github("schemaanalyst/directedRandom-R-pkg")
Within your R environment, use the following commands:
mutants <- directedRandomR::read_mutants()
analysis <- directedRandomR::read_analysis()
x1 <- directedRandomR::table_generator_timing(analysis, rtrn = "data", m = "mean")
x2 <- directedRandomR::table_generator_coverage(analysis, rtrn = "data", m = "mean")
x3 <- directedRandomR::table_generator_mutation_score(mutants, rtrn = "data", m = "mean")
x4 <- directedRandomR::table_generator_mutant_operators(mutants, rtrn = "data", m = "mean")
NOTE: The rtrn
parameter is used to return either a dataframe (rtrn = "data"
) or a latex table (rtrn = "tex"
). The m
parameter is used to print the table as median
or mean
results.
library(directedRandomR)
?read_mutants
?read_analysis()
?table_generator_timing()
?table_generator_coverage()
?table_generator_mutation_score()
?table_generator_mutant_operators()
If you are interested in extending this package with new data sets and your own functions, then you can run the following command to first clone this repository:
git clone https://github.com/schemaanalyst/directedRandom-R-pkg.git
Furthermore, in your R environment, you can run each of the following commands. This will help you to build, install, load, and test our R packages using devtools
:
devtools::document()
devtools::install()
devtools::load_all()
devtools::test()
Whilst running our tests, the following results will appear:
coverages-sample-size: ....
coverages-median-resutlts: ....
coverages-effect-size: ...
coverages-u-test: ...
mutant-operators-sample-size: ........
mutant-operators-mean-results: ............
mutant-operators-u-test-results: ...........
mutant-operators-effect-size-results: ...........
mutant-scores-mean-results: ....
mutant-scores-sample-size: ....
mutant-scores-u-test-results: ...
mutant-scores-effect-size-results: ...
table-generator: ........
testgenerationtiming-sample-size: ....
testgenerationtiming-median-results: ....
testgenerationtiming-u-test-results: ...
testgenerationtiming-effect-size-results: ...
DONE =========================================
The conventions we have used are explained in the following URLs:
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