Book Image

Learn Data Structures and Algorithms with Golang

By : Bhagvan Kommadi
5 (1)
Book Image

Learn Data Structures and Algorithms with Golang

5 (1)
By: Bhagvan Kommadi

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.

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Table of Contents (16 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
Section 1: Introduction to Data Structures and Algorithms and the Go Language
Section 1: Introduction to Data Structures and Algorithms and the Go Language
2
Data Structures and Algorithms
Data Structures and Algorithms
Technical requirements
Classification of data structures and structural design patterns
Representation of algorithms
Complexity and performance analysis
Brute force algorithms
Divide and conquer algorithms
Backtracking algorithms
Summary
Questions and exercises
Further reading
3
Getting Started with Go for Data Structures and Algorithms
Getting Started with Go for Data Structures and Algorithms
Technical requirements
Arrays
Slices
Two-dimensional slices
Maps
Database operations
Variadic functions
CRUD web forms
Summary
Questions
Further reading
4
Section 2: Basic Data Structures and Algorithms using Go
Section 2: Basic Data Structures and Algorithms using Go
5
Linear Data Structures
Linear Data Structures
Technical requirements
Lists
Sets
Tuples
Queues
Stacks
Summary
Questions
Further reading
6
Non-Linear Data Structures
Non-Linear Data Structures
Technical requirements
Trees
Tables
Symbol tables
Containers
The hash functions
Summary
Questions
Further reading
7
Homogeneous Data Structures
Homogeneous Data Structures
Technical requirements
Two-dimensional arrays
Multi-dimensional arrays
Summary
Questions
Further reading
8
Heterogeneous Data Structures
Heterogeneous Data Structures
Technical requirements
Linked lists
Ordered lists
Unordered lists
Summary
Questions
Further reading
9
Dynamic Data Structures
Dynamic Data Structures
Technical requirements
Dictionaries
TreeSets
Sequences
Summary
Questions
Further reading
10
Classic Algorithms
Classic Algorithms
Technical requirements
Sorting
Searching
Recursion
Hashing
Summary
Questions
Further reading
11
Section 3: Advanced Data Structures and Algorithms using Go
Section 3: Advanced Data Structures and Algorithms using Go
12
Network and Sparse Matrix Representation
Network and Sparse Matrix Representation
Technical requirements
Network representation using graphs
Sparse matrix representation using a list of lists
Summary
Questions
Further reading
13
Memory Management
Memory Management
Technical requirements
Garbage collection
Cache management
Space allocation
Concepts – Go memory management
Summary
Questions
Further reading
14
Next Steps
Next Steps
Technical requirements
Learning outcomes
15
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Learning outcomes

The learning outcomes from this book are as follows:

  • Improve a web or mobile application's performance using the correct data structures and algorithms.
  • Understand how an algorithm solves a problem and how the correct data structure is chosen for a problem.
  • Enumerate the various solutions to a problem and identify algorithms and data structures after doing a cost/benefit analysis.
  • Get a grasp of the various techniques for writing pseudocode for an algorithm, allowing you to ace white-boarding sessions and interview assignments.
  • Discover the pitfalls in selecting data structures and algorithms by predicting how fast and efficient an algorithm or data structure is.

In the following section, the key takeaway points, papers, and articles to be referred to, along with tips and techniques, are discussed.

...
Previous Section
End of Chapter 14
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