Prior Shortcomings

Many older random sequence algorithms yield far less than the number of possible unique sequences of a 52-card deck. You often see only 2¹⁶, or 65,536 unique sequences generated by older RNGs, which is far short of the approximately 2²²⁵ needed to cover all possible sequences in a 52-card deck.

Another shortcoming of prior PRNGs is guaranteed periodicity - it is certain that if the generator uses only a fixed amount of memory, then given a sufficient number of iterations, the generator will revisit the same internal state twice, after which it will repeat forever. A generator that isn't periodic can be designed, but its memory requirements would slowly grow as it ran. In addition, a PRNG can be started from an arbitrary starting point, or seed state, and will always produce an identical sequence from that point on. Also, in practice, many prior PRNGs exhibit artifacts which can cause them to fail statistical significance tests. These include:
? Shorter than expected periods for some seed- states
? Poor dimensional distribution
? Successive values may not be independent
? Some bits are more random than others
? Lack of uniformity