How does calling srand more than once affect the quality of randomness?

Question

This comment, which states:

srand(time(0)); I would put this line as the first line in main() instead if calling it multiple times (

Answer 1

A pseudo random generator is an engine which produce numbers that look almost random. However, they are completely deterministic. In other words, given a seed x0, they are produced by repeated application of some injective function on x0, call it f(x0), so that f^m(x0) is quite different from f^{m-1}(x0) or f^{m+1}(x0), where the notation f^m denotes the function composition m times. In other words, f(x) has huge jumps, almost uncorrelated with the previous ones.

If you use sradnd(time) multiple times in a second, you may get the same seed, as the clock is not as fast as you may imagine. So the resulting sequence of random numbers will be the same. And this may be a (huge) problem, especially in cryptography applications (anyway, in the latter case, people buy good number generators based on real-time physical processes such as temperature difference in atmospheric data etc, or, recently, on measuring quantum bits, e.g. superposition of polarized photons, the latter being truly random, as long as quantum mechanics is correct.)

There are also other serious issues with rand. One of it is that the distribution is biased. See e.g. http://eternallyconfuzzled.com/arts/jsw_art_rand.aspx for some discussion, although I remember I've seen something similar on SO, although cannot find it now.

If you plan to use it in crypto applications, just don't do it. Use and a serious random engine like Mersene's twister std::mt19937 combined with std::random_device

If you seed your random number generator twice using srand, and get different seeds, then you will get two sequences that will be quite different. This may be satisfactory for you. However, each sequence per se will not be a good random distribution due to the issues I mentioned above. On the other hand, if you seed your rng too many times, you will get the same seed, and THIS IS BAD, as you'll generate the same numbers over and over again.

PS: seen in the comments that pseudo-numbers depend on a seed, and this is bad. This is the definition of pseudo-numbers, and it is not a bad thing as it allows you to repeat numerical experiments with the same sequence. The idea is that each different seed should produce a sequence of (almost) random numbers, different from a previous sequence (technically, you shouldn't be able to distinguish them from a perfect random sequence).