What Is Graph and Basic Terminology in Data Structure?

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Angela Bailey

Data structure is an essential concept in computer science that allows us to efficiently organize and manage data. One common and widely used data structure is a graph. In this article, we will explore what a graph is and discuss some of the basic terminology associated with it.

What is a Graph?

A graph is a non-linear data structure consisting of a set of vertices (also known as nodes) and a set of edges that connect these vertices. It represents relationships between different objects or entities.

Graphs are widely used in various applications such as social networks, transportation systems, computer networks, and more. They provide a flexible way to model and solve complex problems.

Basic Terminology

Let’s delve into some basic terminology related to graphs:

1. Vertex

A vertex, also known as a node, represents an object or entity in a graph. For example, in a social network graph, each person can be represented by a vertex.

2. Edge

An edge represents the connection or relationship between two vertices. It can be either directed or undirected.

3. Directed Edge

In a directed graph, each edge has a direction associated with it.

It indicates the flow or relationship between two vertices. For example, in a transportation system graph, directed edges can represent one-way roads.

4. Undirected Edge

In an undirected graph, edges have no specific direction associated with them.

The relationship is symmetric between two vertices. For example, in a friendship network, undirected edges represent mutual friendships.

5. Weighted Edge

A weighted edge assigns some value or weight to the connection between two vertices. It represents the strength, distance, or cost associated with that relationship.

6. Degree of a Vertex

The degree of a vertex is the number of edges connected to it. In a directed graph, we have both indegree (incoming edges) and outdegree (outgoing edges).

7. Path

A path in a graph is a sequence of vertices connected by edges. It represents a route or traversal from one vertex to another.

Types of Graphs

Graphs can be classified into various types based on their properties:

  • Directed Graph: Also known as digraph, it consists of directed edges.
  • Undirected Graph: It has undirected edges.
  • Weighted Graph: The edges have weights assigned to them.
  • Cyclic Graph: A graph that contains at least one cycle (a path that starts and ends at the same vertex).
  • Acyclic Graph: It does not contain any cycles.
  • Bipartite Graph: The vertices can be divided into two disjoint sets such that no edge exists between vertices within the same set.

This article provided an introduction to graphs and covered some basic terminology associated with them. Understanding these concepts is crucial for effectively working with graphs and solving problems related to them. By using appropriate data structures like graphs, we can model real-world relationships and build efficient algorithms for various applications.

If you found this article helpful, stay tuned for more in-depth tutorials on data structures and algorithms!

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