6.8. C++11 Random Numbers

According to CERT, function rand does not have “good statistical properties” and can be predictable, which makes programs that use rand less secure (CERT guideline MSC30-CPP). As we mentioned in Section 6.6, C++11 provides a new, more secure library of random-number capabilities that can produce nondeterministic random numbers for simulations and security scenarios where predictability is undesirable. These new capabilities are located in the C++ Standard Library’s <random> header.

Random-number generation is a mathematically sophisticated topic for which mathematicians have developed many random-number generation algorithms with different statistical properties. For flexibility based on how random numbers are used in programs, C++11 provides many classes that represent various random-number generation engines and distributions. An engine implements a random-number generation algorithm that produce pseudorandom numbers. A distribution controls the range of values produced by an engine, the types of those values (e.g., int, double, etc.) and the statistical properties of the values. In this section, we’ll use the default random-number generation engine—default_random_engine—and a uniform_int_distribution, which evenly distributes pseudorandom integers over a specified range of values. The default range is from 0 to the maximum value of an int on your platform.