Software Testing for Data Science in R I often use Nose, Tox or Unittest when testing my python code, specially when it has to be integrated with other modules or other pieces of code. However, now that I've found myself using R more than python for ML modelling and development. I realized that I don't really test my R code (And more importantly I really don't know how to do it well). So my question is, what are good packages that allow you to test R code in a similar manner as Nose, Tox or Unittest do in Python. Additional references such as tutorials will be greatly appreciated as well.

Bonus points for packages in R similar to 


Hypothesis

or
Feature Forge


Related Talk:

Trey Causey: Testing for Data Scientists
Packages for unit testing and assertive testing that are actively maintained:
Packages for unit testing


testthat: more information on how to use you can find here or on github
Runit: Cran page


Packages for assertions:


assertthat: info on github
assertive: Assertive has a lot of subpackages available in case you do not need all of them. check on cran
assertr: info on github
ensurer: info on github
tester: info on github


It is a matter of preference what you want to use for assertions. 
Read this bioconductor page for more info on the difference between RUnit and testthat.