We were computing these functions incorrectly.
I'm not sure what distribution these numbers are, but it isn't the
normal exponential distribution. (We're making the probability of
getting a number of a particular bitlength equal, but the number in
that bitlength thats gets chosen is uniformly chosen)
We weren't using these functions anywhere in our codebase, and they
had a nomenclature error. (There aren't exponentially distributed
integers, instead they would be geometrically distributed)
Lesson articulated by @jaekwon on why we need 80 bits
of entropy at least before we can think of cryptographic
safety. math/rand's seed is a max of 64 bits so can never
be cryptographically secure.
Also added some benchmarks for RandBytes
Fixes https://github.com/tendermint/tmlibs/issues/99
Updates https://github.com/tendermint/tendermint/issues/973
Removed usages of math/rand.DefaultSource in favour of our
own source that's seeded with a completely random source
and is safe for use in concurrent in multiple goroutines.
Also extend some functionality that the stdlib exposes such as
* RandPerm
* RandIntn
* RandInt31
* RandInt63
Also added an integration test whose purpose is to be run as
a consistency check to ensure that our results never repeat
hence that our internal PRNG is uniquely seeded each time.
This integration test can be triggered by setting environment variable:
`TENDERMINT_INTEGRATION_TESTS=true`
for example
```shell
TENDERMINT_INTEGRATION_TESTS=true go test
```
Dev Ojha
Zach Ramsay
Ethan Buchman
Jae Kwon
Emmanuel Odeke