Book Image

Learn Data Structures and Algorithms with Golang

By : Bhagvan Kommadi
Book Image

Learn Data Structures and Algorithms with Golang

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.
Table of Contents (16 chapters)
Free Chapter
Section 1: Introduction to Data Structures and Algorithms and the Go Language
Section 2: Basic Data Structures and Algorithms using Go
Section 3: Advanced Data Structures and Algorithms using Go

Backtracking algorithms

A backtracking algorithm solves a problem by constructing the solution incrementally. Multiple options are evaluated, and the algorithm chooses to go to the next component of the solution through recursion. Backtracking can be a chronological type or can traverse the paths, depending on the problem that you are solving.

Backtracking is an algorithm that finds candidate solutions and rejects a candidate on the basis of its feasibility and validity. Backtracking is useful in scenarios such as finding a value in an unordered table. It is faster than a brute force algorithm, which rejects a large number of solutions in an iteration. Constraint satisfaction problems such as parsing, rules engine, knapsack problems, and combinatorial optimization are solved using backtracking.

The following is an example of a backtracking algorithm. The problem is to identify...