well, that algorithm could offer the best performance in assembler or C but I doubt it could make any difference in Perl.
Actually...
use Benchmark qw(cmpthese);
# insert your code here
sub my_mma {
my $r = shift;
if (@$r) {
my ($min, $max, $tot) = ($r->[0]) x 3;
for (@$r[1..$#$r]) {
$min = $_ if $_ < $min;
$max = $_ if $_ > $max;
$tot += $_;
}
return ($min, $max, $tot/@$r);
}
return (undef, undef, undef)
}
my @nums = map {rand} 1..1000;
cmpthese(-1, { ita => sub { my @r = min_max_avg(\@nums) },
simple => sub { my @r = my_mma(\@nums) } })
runs as...
Rate ita simple
ita 222/s -- -50%
simple 449/s 102% --
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