> As such I would prefer to keep using the carrotsearch generators Works for me; I am cool with the added test dependency.
> On Dec 14, 2022, at 7:13 AM, Mike Adamson <madam...@datastax.com> wrote: > > I have had a look at whether we could use the QuickTheories in our randomized > testing and come to the following conclusions: > > Pros: > 1) It has a very rich set of random generators out of the box. > 2) It has a very powerful mechanism for generating customised randomized > datasets. > 3) It is very pluggable within the constraints of its framework. > > Cons: > 1) The framework has to be used in a very specific way in order for it to > work. It does not allow for subsets of the framework to be used in isolation. > 2) The code hasn't been touched for 3 years. This is an observation as much > as anything but it does not appear to be being maintained at the moment. > > The carrotsearch generators use a seeded Random to generate their values so > are also repeatable. It also provides a very rich set of random generators > that can be used in isolation of any other part of the framework. This > project is also being actively maintained. > > As such I would prefer to keep using the carrotsearch generators. I have made > a change to the SAI testing that removes our usage of RandomizedTest from the > library and have stuck to just using the lower level random generators. We > already had a Randomization class in our test framework that provided a lot > of the RandomizedTest functionality (primarily the reporting on failed tests > of the random seed and the reuse of seeds) so using both made no sense.
