Log message:
Recursive revbump from lang/perl5 5.26.0

Log message:
Bump PKGREVISION for perl-5.24.

Log message:
Add SHA512 digests for distfiles for math category

Problems found locating distfiles:
	Package dfftpack: missing distfile dfftpack-20001209.tar.gz
	Package eispack: missing distfile eispack-20001130.tar.gz
	Package fftpack: missing distfile fftpack-20001130.tar.gz
	Package linpack: missing distfile linpack-20010510.tar.gz
	Package minpack: missing distfile minpack-20001130.tar.gz
	Package odepack: missing distfile odepack-20001130.tar.gz
	Package py-networkx: missing distfile networkx-1.10.tar.gz
	Package py-sympy: missing distfile sympy-0.7.6.1.tar.gz
	Package quadpack: missing distfile quadpack-20001130.tar.gz

Otherwise, existing SHA1 digests verified and found to be the same on
the machine holding the existing distfiles (morden).  All existing
SHA1 digests retained for now as an audit trail.

Log message:
Recursive PKGREVISION bump for all packages mentioning 'perl',
having a PKGNAME of p5-*, or depending such a package,
for perl-5.22.0.

Log message:
Bump for perl-5.20.0.
Do it for all packages that
* mention perl, or
* have a directory name starting with p5-*, or
* depend on a package starting with p5-
like last time, for 5.18, where this didn't lead to complaints.
Let me know if you have any this time.

Log message:
Adding package for CPAN distribution Math-Random-ISAAC version 1.004 into
math/p5-Math-Random-ISAAC.

As with other Pseudo-Random Number Generator (PRNG) algorithms like the
Mersenne Twister (see Math::Random::MT), this algorithm is designed to
take some seed information and produce seemingly random results as output.

However, ISAAC (Indirection, Shift, Accumulate, Add, and Count) has
different goals than these commonly used algorithms. In particular, it's
really fast - on average, it requires only 18.75 machine cycles to generate
a 32-bit value. This makes it suitable for applications where a significant
amount of random data needs to be produced quickly, such solving using the
Monte Carlo method or for games.

The results are uniformly distributed, unbiased, and unpredictable unless
you know the seed. The algorithm was published by Bob Jenkins in the late
90s and despite the best efforts of many security researchers, no feasible
attacks have been found to date.