If a random generator function is not supplied to the random_shuffle algorithm in the standard library, will successive runs of the program produce the same random sequence if supplied with the same data?
For example, if
std::random_shuffle(filenames.begin(), filenames.end());
is performed on the same list of filenames from a directory in successive runs of the program, is the random sequence produced the same as that in the prior run?
If you use the same random generator, with the same seed, and the same starting sequence, the results will be the same. A computer is, after all, deterministic in its behavior (modulo threading issues and a few other odds and ends).
If you do not specify a generator, the default generator is
implementation defined. Most implementations, I think, use
std::rand()
(which can cause problems, particularly when the number of
elements in the sequence is larger than RAND_MAX
). I would recommend
getting a generator with known quality, and using it.
If you don't correctly seed the generator which is being used (another
reason to not use the default, since how you seed it will depend on the
implementation), then you'll get what you get. In the case of
std::rand()
, the default always uses the same seed. How you seed
depends on the generator used. What you use to seed it should be vary
from one run to the other; for many applications, time(NULL)
is
sufficient; on a Unix platform, I'd recommend reading however many bytes
it takes from /dev/random
. Otherwise, hashing other information (IP
address of the machine, process id, etc.) can also improve things---it
means that two users starting the program at exactly the same second
will still get different sequences. (But this is really only relevant
if you're working in a networked environment.)
25.2.11 just says that the elements are shuffled with uniform distribution. It makes no guarantees as to which RNG is used behind the scenes (unless you pass one in) so you can't rely on any such behavior.
In order to guarantee the same shuffle outcome you'll need to provide your own RNG that provides those guarantees, but I suspect even then if you update your standard library the random_shuffle algorithm itself could change effects.
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