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Expert C++

Expert C++

By : Vardan Grigoryan, Shunguang Wu
3.1 (9)
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Expert C++

Expert C++

3.1 (9)
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)
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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

Mastering algorithms

As already mentioned, algorithms are functions taking some input, processing it, and returning an output. Usually, an algorithm in the context of the STL implies a function processing a collection of data. Collections of data are presented in the form of containers, such as std::vector, std::list, and others.

Choosing an efficient algorithm is a common task in a programmer's routine. For example, searching a sorted vector using the binary search algorithm will be much more efficient than using sequential searching. To compare the efficiency of algorithms, a so-called asymptotic analysis is performed, which takes into consideration the speed of the algorithm with regard to the input data size. This means that we shouldn't actually compare two algorithms by applying them to a container with ten or a 100 elements.

The actual difference of algorithms...

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Expert C++
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