This project focuses on the implementation and utilization of various graph theories to analyze and manipulate graphs. Specifically, we employ concepts such as complete graphs, adjacency matrices and degree of a node.
A complete graph, also known as a fully connected graph, is a graph in which there is an edge between every pair of distinct vertices. In this project, we utilize complete graphs to model and analyze various scenarios where every vertex is connected to every other vertex.
An adjacency matrix is a square matrix used to represent a graph. Each entry in the matrix indicates whether there is an edge between the corresponding vertices. In our project, we leverage adjacency matrices to efficiently store and retrieve information about the connectivity of vertices in a graph.
In graph theory, the degree of a node refers to the number of edges incident to that node. It represents the connectivity or centrality of a node within a graph. The degree can be further classified as the in-degree and out-degree for directed graphs.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent