Bhagvan Kommadi is the Founder of Architect Corner & has around 19 years’ experience in the industry, ranging from large scale enterprise development to helping incubate software product start-ups. He has done Masters in Industrial Systems Engineering at Georgia Institute of Technology (1997) and Bachelors in Aerospace Engineering from Indian Institute of Technology, Madras (1993). He is member of IFX forum,Oracle JCP and participant in Java Community Process. He is part of the Acta Scientific Medical Sciences Review Board.

Bhagvan Kommadi founded Quantica Computacao, the first quantum computing startup in India. Markets and Markets have positioned Quantica Computacao in ‘Emerging Companies’ section of Quantum Computing quadrants. Bhagvan has engineered and developed simulators and tools in the area of quantum technology using IBM Q, Microsoft Q#, and Google QScript. Company's focus is on developing quantum cryptographic tools which will be able to provide quantum proof data security, which will help the banking institution to protect their transactions.

He is a hands-on CTO who has been contributing to open source, blogs, latest technologies stack like go, Python, Django, node.js & Java, MySQL, Postgres, Mongo and Cassandra. He is an Individual member of Oracle JCP: https://jcp.org/en/participation/members/K. He is the technical reviewer for Packt publishing and reviewed the book titled building-serverless-python-web-services- zappa. He has written Packt Publishing - Hands-On Data Structures and Algorithms with Go. He is writing books titled Learn-Q-Programming---Fundamentals-of-Q# and Hands-On Quantum Computing with Python. He has presented in PyCon before on topics such as Adaptive Learning etc.,

Explore Golang's data structures and algorithms to design, implement, and analyze code in the professional setting

Key Features

Learn the basics of data structures and algorithms and implement them efficiently

Use data structures such as arrays, stacks, trees, lists and graphs in real-world scenarios

Compare the complexity of different algorithms and data structures for improved code performance

Book Description

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.

What you will learn

Improve application performance using the most suitable data structure and algorithm

Explore the wide range of classic algorithms such as recursion and hashing algorithms

Work with algorithms such as garbage collection for efficient memory management

Analyze the cost and benefit trade-off to identify algorithms and data structures for problem solving

Explore techniques for writing pseudocode algorithm and ace whiteboard coding in interviews

Discover the pitfalls in selecting data structures and algorithms by predicting their speed and efficiency

Who this book is for

This book is for developers who want to understand how to select the best data structures and algorithms that will help solve coding problems. Basic Go programming experience will be an added advantage.

Table of Contents

Data Structures & Algorithms

Getting Started with Go for Data Structures & Algorithms

Linear Data Structures

Non Linear Data Structures

Homogeneous Data Structures

Heterogeneous Data Structures

Dynamic Data Structures

Classic Algorithms

Network and Sparse Matrix Representation

Memory Management

Next Steps (Appendix)