Data Structures and Algorithms

A data structure is the organization of data to reduce the storage space used and to reduce the difficulty while performing different tasks. Data structures are used to handle and work with large amounts of data in various fields, such as database management and internet indexing services.

In this chapter, we will focus on the definition of abstract datatypes, classifying data structures into linear, nonlinear, homogeneous, heterogeneous, and dynamic types. Abstract datatypes, such as Container, List, Set, Map, Graph, Stack, and Queue, are presented in this chapter.  We will also cover the performance analysis of data structures, choosing the right data structures, and structural design patterns.

The reader can start writing basic algorithms using the right data structures in Go. Given a problem, choosing the data structure and different algorithms will be the first step. After this, doing performance analysis is the next step. Time and space analysis for different algorithms helps compare them and helps you choose the optimal one. It is essential to have basic knowledge of Go to get started. 

In this chapter, we will cover the following topics:

• Classification of data structures and structural design patterns
• Representation of algorithms
• Complexity and performance analysis
• Brute force algorithms
• Divide and conquer algorithms
• Backtracking algorithms