CODEWITHSUNDEEP
crandomrandom-seed
Kaiyaha
Kaiyaha

Reputation: 480

Does rand() indeed produce a random value when the random number generator has been seeded?

I know that in order to avoid repeating the same output of the rand() function a pseudo-random number generator must be seeded with the srand function. That means, if I try say srand(1), the output of the rand() will be one value, if I try srand(2), the output will contain another value. But when I try the first argument again like srand(1), the value will be the same as in the first output. This issue made me think that all random values would be predictable in some way. Is it possible to have different output for the same seed (say if I try the same seed tomorrow)? Or are random values predictable indeed?

Upvotes: 1

Views: 396

Answers (2)

chqrlie
chqrlie

Reputation: 144740

Here is the language of the C Standard:

7.22.2 Pseudo-random sequence generation functions

7.22.2.1 The rand function

Synopsis

 #include <stdlib.h>
 int rand(void);

The rand function computes a sequence of pseudo-random integers in the range 0 to RAND_MAX The rand function is not required to avoid data races with other calls to pseudo-random sequence generation functions. The implementation shall behave as if no library function calls the rand function.

Returns

The rand function returns a pseudo-random integer.

Environmental limits

The value of the RAND_MAX macro shall be at least 32767.

7.22.2.2 The srand function

Synopsis

#include <stdlib.h>
void srand(unsigned int seed);

The srand function uses the argument as a seed for a new sequence of pseudo-random numbers to be returned by subsequent calls to rand. If srand is then called with the same seed value, the sequence of pseudo-random numbers shall be repeated. If rand is called before any calls to srand have been made, the same sequence shall be generated as when srand is first called with a seed value of 1.

The srand function is not required to avoid data races with other calls to pseudo-random sequence generation functions. The implementation shall behave as if no library function calls the srand function.

Returns

The srand function returns no value.

In other words, rand() returns a pseudo-random sequence of integers between 0 and RAND_MAX. The sequence is not random, it is predictable for every value passed to srand(), including if srand() is never called.

In order to try and get different sequences for successive runs of the program, srand() can be called with a rapidly varying value, such as the return value of clock(). Note that calling srand(time(NULL)) will produce the same sequence for multiple runs of the program during the same second.

Upvotes: 2

templatetypedef
templatetypedef

Reputation: 372784

With the traditional definition of a pseudorandom generator, if you know what the generator has been seeded with, then the sequence of output values is completely determined and not random. This means that if you knew the seed for a random generator, then you could predict every single output that generator would produce from that point forward. (A good random number generator is one where seeing a sequence of outputs of the generator does not let you easily reverse-engineer what the random seed is or predict other values.)

I seem to remember reading a while back that, a while back, some popular poker websites were not doing a good job choosing their random seeds. Some people figured out that you could input the pattern of cards you were seeing, and the system could then reverse-engineer the random seed and let you predict all the future cards. Oops. These days, we have cryptographically secure pseudorandom generators based on encryption routines that, at least when it comes to what's known in the open literature, can't be predicted even if you have gigabytes of random bits of output from the generators.

If you do need to get something that really isn't predictable - that is, you want to get a bunch of truly random bits - you'll need to use something other than a pseudorandom number generator. Most operating systems have some mechanism in place to generate values that do appear to be truly random. They might, for example, look at how long it takes for different capacitors to discharge on the motherboard, or factor in timing information from a clock, or see how the user interacts with the keyboard, etc. These data can be fed into something called an entropy accumulator that slowly builds up more and more random bits. If you need a value that's truly random and can't be predicted in advance, you can check your particular OS for the mechanism used to get data from the entropy accumulator. (You can read from /dev/random on UNIX-style machines, for example.)

Often, pulling data from the entropy accumulator takes time, since the computer has to wait long enough for enough different sources to mix together to give you back high-quality random data. A common strategy, therefore, is to use the entropy accumulator to get a high-quality random seed, then "stretch" the randomness by using it as the seed of a strong pseudorandom generator.

Upvotes: 6

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