#### Overview of this book

Golang is one of the fastest growing programming languages in the software industry. Its speed, simplicity, and reliability make it the perfect choice for building robust applications. This brings the need to have a solid foundation in data structures and algorithms with Go so as to build scalable applications. Complete with hands-on tutorials, this book will guide you in using the best data structures and algorithms for problem solving. The book begins with an introduction to Go data structures and algorithms. You'll learn how to store data using linked lists, arrays, stacks, and queues. Moving ahead, you'll discover how to implement sorting and searching algorithms, followed by binary search trees. This book will also help you improve the performance of your applications by stringing data types and implementing hash structures in algorithm design. Finally, you'll be able to apply traditional data structures to solve real-world problems. By the end of the book, you'll have become adept at implementing classic data structures and algorithms in Go, propelling you to become a confident Go programmer.
Preface
Free Chapter
Section 1: Introduction to Data Structures and Algorithms and the Go Language
Data Structures and Algorithms
Getting Started with Go for Data Structures and Algorithms
Section 2: Basic Data Structures and Algorithms using Go
Linear Data Structures
Non-Linear Data Structures
Homogeneous Data Structures
Heterogeneous Data Structures
Dynamic Data Structures
Classic Algorithms
Section 3: Advanced Data Structures and Algorithms using Go
Network and Sparse Matrix Representation
Memory Management
Next Steps
Other Books You May Enjoy

# Network representation using graphs

A graph is a representation of a set of objects that's connected by links. The links connect vertices, which are points. The basic operations on a graph are the addition and removal of links and vertices. These are some different types of graphs:

• Directed graph
• Non-directed graph
• Connected graph
• Non-connected graph
• Simple graph
• Multi-graph

An adjacency list consists of adjacent vertices of a graph that have objects or records. An adjacency matrix consists of source and destination vertices. An incidence matrix is a two-dimensional Boolean matrix. The matrix has rows of vertices and columns that represent the links (edges).

Network representation using a graph is shown in the following code. A social graph consists of an array of links:

`///main package has examples shown// in Go Data Structures and algorithms bookpackage main// importing...`