In mathematics, computer science and digital electronics, a dependency graph is a directed graph representing dependencies of several objects towards each other. It is possible to derive an evaluation order or the absence of an evaluation order that respects the given dependencies from the dependency graph.
Given a set of objects and a transitive relation with modeling a dependency "a depends on b" ("a needs b evaluated first"), the dependency graph is a graph with the transitive reduction of R.
For example, assume a simple calculator. This calculator supports assignment of constant values to variables and assigning the sum of exactly two variables to a third variable. Given several equations like "A = B+C; B = 5+D; C=4; D=2;", then and . You can derive this relation directly: A depends on B and C, because you can add two variables if and only if you know the values of both variables. Thus, B must be calculated before A can be calculated. However, the values of C and D are known immediately, because they are number literals.
In a dependency graph, the cycles of dependencies (also called circular dependencies) lead to a situation in which no valid evaluation order exists, because none of the objects in the cycle may be evaluated first. If a dependency graph does not have any circular dependencies, it forms a directed acyclic graph, and an evaluation order may be found by topological sorting. Most topological sorting algorithms are also capable of detecting cycles in their inputs; however, it may be desirable to perform cycle detection separately from topological sorting in order to provide appropriate handling for the detected cycles.
Assume the simple calculator from before. The equation system "A=B; B=D+C; C=D+A; D=12;" contains a circular dependency formed by A, B and C, as B must be evaluated before A, C must be evaluated before B, and A must be evaluated before C.
A correct evaluation order is a numbering of the objects that form the nodes of the dependency graph so that the following equation holds: with .
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In computer science, a topological sort or topological ordering of a directed graph is a linear ordering of its vertices such that for every directed edge uv from vertex u to vertex v, u comes before v in the ordering. For instance, the vertices of the graph may represent tasks to be performed, and the edges may represent constraints that one task must be performed before another; in this application, a topological ordering is just a valid sequence for the tasks.
In mathematics, particularly graph theory, and computer science, a directed acyclic graph (DAG) is a directed graph with no directed cycles. That is, it consists of vertices and edges (also called arcs), with each edge directed from one vertex to another, such that following those directions will never form a closed loop. A directed graph is a DAG if and only if it can be topologically ordered, by arranging the vertices as a linear ordering that is consistent with all edge directions.
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