package Analizo::Metric::AverageCycloComplexity;
use strict;
use parent qw(Class::Accessor::Fast Analizo::ModuleMetric);
use Statistics::Descriptive;

Analizo::Metric::AverageCycloComplexity - Average Cyclomatic Complexity per Method (ACCM) metric

The metric calculation is based on the following article and calculates the
cyclomatic complexity of the program.

Article:
I<McCabe, Thomas J. "A complexity measure." IEEE Transactions on software Engineering 4 (1976): 308-320>.

The Average Cyclomatic Complexity per Method is calculated counting the
predicates (i.e., decision points, or conditional paths) on each method plus
one, then a mean of all methods is returned as the final value of ACCM.

The cyclomatic complexity of a program represented as a graph can be calculated
using a formula of graph theory:

v(G) = e - n + 2

Where C<e> is the number of edges and C<n> is the number of nodes of the graph.

Another good reference is:
I<Woodward, Martin R., Michael A. Hennell, and David Hedley. "A measure of control flow complexity in program text." IEEE Transactions on Software Engineering 1 (1979): 45-50>.

=cut

__PACKAGE__->mk_accessors(qw( model ));

sub new {
my (\$package, %args) = @_;
my @instance_variables = (
model => \$args{model}
);
return bless { @instance_variables }, \$package;
}

sub description {
return 'Average Cyclomatic Complexity per Method';
}

sub calculate {
my (\$self, \$module) = @_;

my @functions = \$self->model->functions(\$module);
if (scalar(@functions) == 0) {
return 0;
}

my \$statisticalCalculator = Statistics::Descriptive::Full->new();
for my \$function (@functions) {