- The C Standard Library
. Configuring the /dev/random driver under Linux. The /dev/random driver under Linux uses minor numbers 8 and 9 of. the /dev/mem major number (#1). So if your system does not have. /dev/random and /dev/urandom created already, they can be created. by using the commands:. mknod /dev/random c 1 8. mknod /dev/urandom c 1 9.
- C Standard Library Resources
- C Programming Resources
This function reads from /dev/random to obtain an array of cryptographically-secure random bytes. For more information on the /dev/random random-number generator, see the manual page for random(4). But that comment is not to be found on the linked documentation, note the post was from Feb 13th, 2017. Conclusion – Random Number Generator in C. In this article we have learned what is a random number generator, needs of random number generator, built-in functions of C to achieve this, with and without using the randomize function, significance of the standard library stdlib.h, step by step instructions to write the code and finally comparison of the outputs of two different approaches.
- Selected Reading
Description
The C library function void srand(unsigned int seed) seeds the random number generator used by the function rand.
Declaration
Following is the declaration for srand() function.
Parameters
seed − This is an integer value to be used as seed by the pseudo-random number generator algorithm.
Return Value
This function does not return any value.
Example
The following example shows the usage of srand() function.
Let us compile and run the above program that will produce the following result −
# Basic Random Number Generation
The function rand() can be used to generate a pseudo-random integer value between 0 and RAND_MAX (0 and RAND_MAX included).
srand(int) is used to seed the pseudo-random number generator. Each time rand() is seeded wih the same seed, it must produce the same sequence of values. It should only be seeded once before calling rand(). It should not be repeatedly seeded, or reseeded every time you wish to generate a new batch of pseudo-random numbers.
Standard practice is to use the result of time(NULL) as a seed. If your random number generator requires to have a deterministic sequence, you can seed the generator with the same value on each program start. This is generally not required for release code, but is useful in debug runs to make bugs reproducible.
It is advised to always seed the generator, if not seeded, it behaves as if it was seeded with srand(1).
Possible output:
Notes:
The C Standard does not guarantee the quality of the random sequence produced. In the past, some implementations of rand() had serious issues in distribution and randomness of the generated numbers. The usage of rand() is not recommended for serious random number generation needs, like cryptography.
# Permuted Congruential Generator
Here's a standalone random number generator that doesn't rely on rand() or similar library functions.
Why would you want such a thing? Maybe you don't trust your platform's builtin random number generator, or maybe you want a reproducible source of randomness independent of any particular library implementation.
This code is PCG32 from pcg-random.org, a modern, fast, general-purpose RNG with excellent statistical properties. It's not cryptographically secure, so don't use it for cryptography.
And here's how to call it:
# Restrict generation to a given range
Usually when generating random numbers it is useful to generate integers within a range, or a p value between 0.0 and 1.0. Whilst modulus operation can be used to reduce the seed to a low integer this uses the low bits, which often go through a short cycle, resulting in a slight skewing of distribution if N is large in proportion to RAND_MAX.
The macro
produces a p value on 0.0 to 1.0 - epsilon, so
C Dev Random Number
will set i to a uniform random number within the range 0 to N - 1.
Unfortunately there is a technical flaw, in that RAND_MAX is permitted to be larger than a variable of type double can accurately represent. This means that RAND_MAX + 1.0 evaluates to RAND_MAX and the function occasionally returns unity. This is unlikely however.
C++ Dev Download
# Xorshift Generation
A good and easy alternative to the flawed rand() procedures, is xorshift, a class of pseudo-random number generators discovered by George Marsaglia. The xorshift generator is among the fastest non-cryptographically-secure random number generators. More information and other example implementaions are available on the xorshift Wikipedia page
Example implementation
# Remarks
Dev C Random Number Generator
Due to the flaws of rand(), many other default implementations have emerged over the years. Among those are:
arc4random()(available on OS X and BSD)random()(available on Linux)drand48()(available on POSIX)