Random Number Generation in C
There are two main ways to generate random numbers in C. 1. Use the rand() function in
Generating random numbers is a common requirement in C programming, such as it is used in game development, simulation programs or test data generation. C provides several ways to do this, but it is easy to write code that is not effective or even wrong without understanding the mechanism behind it.

Use the rand()
function in <cstdlib></cstdlib>
This is the oldest but also the most common method. rand()
returns an integer between 0 and RAND_MAX
(usually 32767).
#include <iostream> #include <cstdlib> #include <ctime> int main() { std::srand(std::time(0)); // Set random seed int randomNum = std::rand(); // Generate random number std::cout << randomNum << std::endl; return 0; }
-
srand()
is used to set the seed. If a different seed is used for each run (such as the current time), the random sequence generated each time the program runs will be different. - If
srand()
is not called, the program will generate the same "random" sequence every time it runs. - The problem with this method is uniformity and predictability, and is not suitable for scenarios with high quality requirements.
Using C11's <random>
library
If you are using C 11 or later, it is recommended to use a more modern <random>
library, which provides more control and better quality of randomness.

#include <iostream> #include <random> int main() { std::random_device rd; // Hardware entropy source, used to generate seed std::mt19937 gen(rd()); // Engine using Mason's rotation algorithm std::uniform_int_distribution<> distrib(1, 100); // Range [1, 100] int randomNum = distrib(gen); std::cout << randomNum << std::endl; return 0; }
-
std::random_device
is a nondeterministic random number generator that is commonly used to initialize other engines. -
std::mt19937
is a commonly used pseudo-random number generator with long cycles and fast speeds. - Distribution objects such as
uniform_int_distribution
can control the range and distribution type of generated numbers (such as normal distribution, Poisson distribution, etc.).
Common misunderstandings and precautions
- Don't repeatedly set seeds : for example, call
srand(time(0))
repeatedly in a loop, which will cause the generated sequence to become "less random". - Avoid direct modulo control range : Writing such as
rand() % 100
can cause uneven distribution, especially if the range is not a factor of RAND_MAX 1. - C 11's
<random>
is more reliable : Although the code is a little more complex, it can provide better randomness and flexibility, suitable for most application scenarios. - Cross-platform behavior may be different : especially the implementation of
rand()
, which may behave inconsistently among different compilers.
Basically that's it. Random number generation seems simple, but to be really good, you still need to pay attention to details.
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