Book Image

Expert C++

By : Vardan Grigoryan, Shunguang Wu
5 (1)
Book Image

Expert C++

5 (1)
By: Vardan Grigoryan, Shunguang Wu

Overview of this book

C++ has evolved over the years and the latest release – C++20 – is now available. Since C++11, C++ has been constantly enhancing the language feature set. With the new version, you’ll explore an array of features such as concepts, modules, ranges, and coroutines. This book will be your guide to learning the intricacies of the language, techniques, C++ tools, and the new features introduced in C++20, while also helping you apply these when building modern and resilient software. You’ll start by exploring the latest features of C++, and then move on to advanced techniques such as multithreading, concurrency, debugging, monitoring, and high-performance programming. The book will delve into object-oriented programming principles and the C++ Standard Template Library, and even show you how to create custom templates. After this, you’ll learn about different approaches such as test-driven development (TDD), behavior-driven development (BDD), and domain-driven design (DDD), before taking a look at the coding best practices and design patterns essential for building professional-grade applications. Toward the end of the book, you will gain useful insights into the recent C++ advancements in AI and machine learning. By the end of this C++ programming book, you’ll have gained expertise in real-world application development, including the process of designing complex software.
Table of Contents (22 chapters)
1
Section 1: Under the Hood of C++ Programming
7
Section 2: Designing Robust and Efficient Applications
17
Section 3: C++ in the AI World

Exploring trees and graphs

The binary search algorithm and sorting algorithms combined together lead to the idea of having a container that keeps items sorted by default. One such container is the std::set, based on a balanced tree. Before discussing the balanced tree itself, let's take a look at the binary search tree, a perfect candidate for fast lookups.

The idea of the binary search tree is that the values of the left-hand subtree of a node are less than the node's value. By contrast, the values of the right-hand subtree of a node are greater than the node's value. Here's an example of a binary search tree:

As you can see in the preceding diagram, the element with the value 15 resides in the left-hand subtree because it's less than 30 (the root element). On the other hand, the element with the value 60 resides in the right-hand subtree because it...