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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

B-trees

A B-tree is a self-balancing tree data structure through which you can organize search, insertion, deletion, and sequential access in logarithmic time. For some operations, the time is not always logarithmic. In the previous chapter, we learned about the time complexity of the std::vector container’s push_back() function. When calculating it, we mentioned that it was amortized, O(1). The same happens for B-trees. Performing deletion and insertion on a B-tree takes amortized O(log n) time. The B-tree is a generalization of the binary search tree that allows nodes to have multiple children. The number of children and keys that a node of a B-tree can hold depends on what order it is in. According to Knuth’s definition, a B-tree of order m is a tree that satisfies the following properties:

  • Every node has at most m children
  • Every internal node has at least {m/2} children
  • Every non-leaf node has at least two children
  • All leaves appear on the same...
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Expert C++
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