R is a statistical programming language, with a strong focus on mathematical operations. When writing code that is math-heavy, unit testing becomes very appealing- while equations may look correct on paper, one minor error can ruin the output. <\/p>\n
R programming is also different to CRUD or enterprise software in that the R in-memory data structures are often used in a similar fashion to a database. When used this way, it is more self-contained, and integration tests that require specific data set-up can be easier to manage than tests that require pre-configured data in a database (a requirement, for instance, when testing some parts of ETL scripts).<\/p>\n
R has a unit testing package called RUnit, based on the JUnit 3.x APIs, which even includes code coverage. Like jUnit, test functions start with the word “test”, and there are startup\/teardown methods.<\/p>\n
Unlike jUnit and nUnit, there is no IDE integration, nor is there a specialized tool – it is simply run through the R REPL, which gives you some control at the expense of convenience. Unfortunately there are no one-click installs with CI servers like Jenkins- if you wish to run tests automatically and track the results over time, you have to figure out some command line integration.<\/p>\n
Unit testing is not designed for fuzzy operations that have natural failures; for a machine learning exercise you ideally may want to track accuracy, recall, precision, etc. This package may be a useful starting point for that, but would require custom development on top to be really valuable for these types of problem.<\/p>\n
The following code will run a test suite, <\/p>\n
\nsource('chords.r')\n\ntest.suite <- defineTestSuite(\"example\",\n dirs = file.path(\"tests\"),\n testFileRegexp = '^.+\\\\.r$')\n\ntest.result <- runTestSuite(test.suite)\n\nprintTextProtocol(test.result)\n\ntest.result\n<\/pre>\nThis prints a result like this:<\/p>\n
\nNumber of test functions: 168\nNumber of errors: 2\nNumber of failures: 166 \n<\/pre>\nBy default R does not print stack traces when there is an error, so the following may be helpful:<\/p>\n
\noptions(error=function() traceback(10))\n\n<\/pre>\nRUnit provides a series of \"check\" functions, for test result assertions:<\/p>\n
\ncheckTrue(x > 0)\n<\/pre>\nThe results are available as text or HTML, or you can inspect the R object, for custom output.<\/p>\n
\nprintTextProtocol(test.result)\n\nstr(test.result)\nList of 1\n$ example:List of 8\n ..$ nTestFunc : num 168\n ..$ nDeactivated : int 0\n ..$ nErr : num 2\n ..$ nFail : num 166\n ..$ dirs : chr \"tests\"\n ..$ testFileRegexp : chr \"^.+\\\\.r$\"\n ..$ testFuncRegexp : chr \"^test.+\"\n ..$ sourceFileResults:List of 1\n .. ..$ tests\/wiki-chords.r:List of 168\n .. .. ..$ testA :List of 4\n .. .. .. ..$ kind : chr \"failure\"\n .. .. .. ..$ msg : chr \"Error in checkTrue(cmp) : Test not TRUE\\n\\n\"\n .. .. .. ..$ checkNum : num 1\n .. .. .. ..$ traceBack: NULL\n .. .. ..$ testA7 :List of 4\n .. .. .. ..$ kind : chr \"failure\"\n .. .. .. ..$ msg : chr \"Error in checkTrue(cmp) : Test not TRUE\\n\\n\"\n .. .. .. ..$ checkNum : num 1\n .. .. .. ..$ traceBack: NULL\n<\/pre>\n