id summary reporter owner description type status priority milestone component version resolution keywords cc os architecture failure difficulty testcase blockedby blocking related
3575 mkStdGen and split conspire to make some programs predictable rwbarton rrnewton "The following program `random.hs` is intended to produce a line containing 30 random 0s or 1s. It is not an example of the best way to use System.Random, but it looks innocuous enough.
{{{
import Control.Monad
import System.Random
print0or1 = do
g <- newStdGen
putStr . show . fst $ randomR (0, 1 :: Int) g
main = replicateM_ 30 print0or1 >> putStrLn """"
}}}
Let's try running it a thousand times:
{{{
rwbarton@functor:/tmp$ ghc-6.10.1 -O2 --make random
[1 of 1] Compiling Main ( random.hs, random.o )
Linking random ...
rwbarton@functor:/tmp$ for i in `seq 1 1000` ; do ./random >> random.out ; done
rwbarton@functor:/tmp$ sort random.out | uniq | wc -l
60
}}}
That's odd... there are 2^30^ possible output lines, but when I tried to generate 1000 random ones, I only got 60 distinct outputs. Why did that happen?
One might think this is due to poor initial seeding of the random number generator (due to the time not changing very much during the test), but this is not the case. Attached is a fancier version of the program which reads an initial seed from `/dev/urandom`; it exhibits the same behavior.
This phenomenon is not too hard to explain. It is ultimately due to a poor interaction between `mkStdGen` and `split`. First, we need to know a bit about the design of System.Random (some statements simplified slightly for this discussion).
* The state of the RNG consists of two `Int32`s, `s1` and `s2`.
* The initial state produced by mkStdGen almost always has `s2` equal to 1. (Extremely rarely, it might have `s2` equal to 2. We'll ignore this as it doesn't affect the argument.)
* To generate a random 0 or 1, we first generate a new state using some simple functions `s1' = next1(s1)`, `s2' = next2(s2)`. (Note that `s1` and `s2` ""evolve"" independently.) The random value returned is the lowest bit of `s1'` minus `s2'`.
* Splitting the generator `(s1, s2)` yields the two generators `(s1+1, next2(s2))` and `(next1(s1), s2-1)`.
Our program functions as follows.
* Initialize the generator stored in `theStdGen` (`s1` is some varying value `a`, `s2` is 1).
* Repeatedly split the generator, replacing it with the first output, and use the second output to generate a 0 or 1.
If we watch `theStdGen` while our program runs, we will see that `s1` is incremented by 1 at each step, while `s2` follows the fixed sequence `1`, `next2(1)`, `next2(next2(1))`, etc. The 0 or 1 we output at the `k`th step is thus the lowest bit of `next1(next1(a+k-1))` minus `b`,,k,,, where `b`,,k,, is some fixed sequence. And as `k` varies, `next1(next1(a+k-1))` turns out to be just an arithmetic sequence with fixed difference modulo a fixed prime so its lowest bits are extremely predictable even without knowing `a`.
This issue can be fixed to some extent, without breaking backwards compatibility, by adding another method (besides `mkStdGen`) to create a generator, which does not have predictable `s2`, and using it to initialize the system RNG." bug new normal ⊥ libraries/random 6.10.1 Unknown/Multiple Unknown/Multiple None/Unknown Unknown