Book Image

Modern C++ Programming Cookbook - Second Edition

By : Marius Bancila
5 (1)
Book Image

Modern C++ Programming Cookbook - Second Edition

5 (1)
By: Marius Bancila

Overview of this book

C++ has come a long way to be one of the most widely used general-purpose languages that is fast, efficient, and high-performance at its core. The updated second edition of Modern C++ Programming Cookbook addresses the latest features of C++20, such as modules, concepts, coroutines, and the many additions to the standard library, including ranges and text formatting. The book is organized in the form of practical recipes covering a wide range of problems faced by modern developers. The book also delves into the details of all the core concepts in modern C++ programming, such as functions and classes, iterators and algorithms, streams and the file system, threading and concurrency, smart pointers and move semantics, and many others. It goes into the performance aspects of programming in depth, teaching developers how to write fast and lean code with the help of best practices. Furthermore, the book explores useful patterns and delves into the implementation of many idioms, including pimpl, named parameter, and attorney-client, teaching techniques such as avoiding repetition with the factory pattern. There is also a chapter dedicated to unit testing, where you are introduced to three of the most widely used libraries for C++: Boost.Test, Google Test, and Catch2. By the end of the book, you will be able to effectively leverage the features and techniques of C++11/14/17/20 programming to enhance the performance, scalability, and efficiency of your applications.
Table of Contents (16 chapters)
13
Bibliography
14
Other Books You May Enjoy
15
Index

Initializing all bits of internal state of a pseudo-random number generator

In the previous recipe, we looked at the pseudo-random number library, along with its components, and how it can be used to produce numbers in different statistical distributions. One important factor that was overlooked in that recipe is the proper initialization of the pseudo-random number generators.

With careful analysis (that is beyond the purpose of this recipe or this book), it can be shown that the Mersenne twister engine has a bias toward producing some values repeatedly and omitting others, thus generating numbers not in a uniform distribution, but rather in a binomial or Poisson distribution. In this recipe, you will learn how to initialize a generator in order to produce pseudo-random numbers with a true uniform distribution.

Getting ready

You should read the previous recipe, Generating pseudo-random numbers, to get an overview of what the pseudo-random number library offers...