## Overall improvement for randomIvalInteger

The current `randomIvalInteger`

implementation uses repeated `div`

operations to approximate the size of the desired random output, then generates that number of random values from the given `RandomGen`

. It does not compensate for the ``mod` base`

uniformity problem. It also assumes that all `RandomGen` implementations produce the same range of random values as `StdGen`.

My new implementation addresses all these correctness issues, with potentially a slight performance improvement.

Instead of performing repeated div base operations to determine the size of the desired range, this uses faster `(* base)`

operations. An equivalent set of intermediate `Integer`

s is generated still.

To compensate for the ``mod` base`

uniformity problem, the desired range size is multiplied by the *q* factor (1000 in my code). When *k* is the desired range and *b^n^* is the range of numbers generated, and *d = b^n^ div k*, some elements will have probability *d/b^n^* and others will have probability *(d+1)/b^n^*, resulting in significant non-uniformity when *d* is very small. When you extend the generated range beyond the minimum by a factor of *q*, you are guaranteed that *d* will be at least *q*, so the non-uniformity will be much less consequential.

This implementation also works with any `RandomGen`

, even ones that produce as little as a single bit of entropy per next call or have a minimum bound other than zero.