mukesh-kk / graph-cpp

Graph

You can get general alogorithms of graph in this repo.

• Transversal
• Searching

A graph data structure is a collection of nodes or vertices interconnected by edges. It is a fundamental data structure used to represent relationships between objects. Graphs are widely used in various fields, including computer science, mathematics, social networks, transportation systems, and more.

In a graph, each node represents an entity, and the edges represent the connections or relationships between the entities. The edges can be directed or undirected, indicating the presence or absence of a specific relationship. For example, in a social network graph, the nodes can represent individuals, and the edges can represent friendships.

There are two common types of graphs:

1. Directed Graph (Digraph): In a directed graph, the edges have a specific direction associated with them. This means that the relationship between two nodes is asymmetric. If there is an edge from node A to node B, it does not necessarily mean that there is an edge from B to A.

2. Undirected Graph: In an undirected graph, the edges have no specific direction. The relationship between two nodes is symmetric. If there is an edge connecting node A and node B, it implies that there is an edge connecting node B and node A.

Graphs can also have weighted edges, where each edge has a weight or cost associated with it. This weight can represent various quantities, such as distance, cost, or strength of the relationship between nodes.

Graphs can be implemented using various data structures, including adjacency matrix, adjacency list, and edge list. Each representation has its advantages and disadvantages in terms of space complexity and performance for different types of operations.

Common operations performed on graphs include traversing the graph, finding paths between nodes, detecting cycles, and calculating various graph properties such as degrees, connected components, and shortest paths.

Graph algorithms, such as depth-first search (DFS), breadth-first search (BFS), Dijkstra's algorithm, and minimum spanning tree algorithms, are used to solve problems and extract useful information from graph structures.