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Alex Balhatchet > Algorithm-DependencySolver > Algorithm::DependencySolver


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Algorithm::DependencySolver - A dependency solver for scheduling access to a shared resource


version 1.01


    use Algorithm::DependencySolver::Solver;
    use Algorithm::DependencySolver::Traversal;
    use Algorithm::DependencySolver::Operation;

    my @operations = (
            id            => 1,
            depends       => [qw(z)],
            affects       => [qw(x)],
            prerequisites => ["3"],
            id            => 2,
            depends       => [qw(x)],
            affects       => [qw(y)],
            prerequisites => [],
            id            => 3,
            depends       => [qw(y)],
            affects       => [qw(z)],
            prerequisites => [],

    my $solver =
        Algorithm::DependencySolver::Solver->new(nodes => \@operations);


    my $traversal = Algorithm::DependencySolver::Traversal->new(
        Solver => $solver,
        visit  => sub {
            my $operation = shift;
            print "Visited operation: ", $operation->id, "\n";



This dependency solver is somewhat different to the existing Algorithm::Dependency module.

Algorithm::Dependency creates a heirarchy where each node depends on a set of other nodes. In Algorithm::DependencySolver, there exists a set of operations and a set of resources, with a set of edges from operations to resources (the dependencies), and a set of edges from resources to operations (the affects). Given this input, the module outputs a directed acyclic graph (DAG) containing just the operations as its nodes.

Aditionally, Algorithm::DependencySolver allows for input which whould have resulted in a cyclic output graph to be resolved by means of explicit sequencing. This is done by marking nodes as depending on other nodes. See Algorithm::DependencySolver::Operation::prerequisites.



Returns the dependency graph as a Graph object. Note that only operations are included in the graph, not resources. This is of most use to the Algorithm::DependencySolver::Traversal module, and the to_dot and to_png methods.


  $self->_remove_redundancy($G);  # Ignore the return value

Applied to a graph object, removes redundant edges. An edge is redundant if it can be removed without invalidating the graph.

The fundamental law of the dependency graph is that a node can only be traversed when all of its predecessors have been traversed.

Given some node, $n, and a predecessor of $n, $a, then it is safe to remove $a if and only if another node exists, $b, which is a predecessor of $n, and there is a path from $a to $b (i.e., traversal of $b requires that $a has been visited).

Note that cycles may cause this algorithm to behave unexpectedly (depending on what one expects). Consider what happens if $n has two successors, $a and $b, such that there is a cycle between $a and $b (i.e., there is an edge from $a to $b, and vice-versa). Suppose that the edge from $n to $a has been removed. Can the edge from $n to $b safely be removed?

Using the algorithm described above, yes! This is because there is another path from $n to $b: $n -> $b -> $a -> b. We can, of course, detect such occurrences; however, I choose not to, because it's not clear to me what the most elegant result should be in these situations. Semantically, it does not matter whether the edge from $n to the $a,$b-cycle is from $n to $a, or $n to $b. Which should it be? Both, or one-or-the-other (presumably decided arbitrarily)?


* This method can be safely called on cyclic graphs (i.e., it will not enter a non-terminating loop)

* This method will not fail early if a cycle is encountered (i.e., it will do as much work as it can, even though the graph is probably invalid)

* If _apply_orderings is to be called on the graph object, it must be done before calling _remove_redundancy



Outputs a dependency graph (showing only operations) to the given file in PNG format



Outputs a dependency graph (showing only operations) to the given file in Graphviz's dot format

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