How to compare randomness of two sets of data? Given two sets of random numbers, is it possible to say that one set of random numbers has a greater degree of randomness when compared to the other?
Or one set of numbers is more random when compared to the other?
EDIT:
Consider this situation:
A hacker needs to know the target address where a heap/library/base of the executable is located. Once he knows the address he can take advantage of it and compromise the system.
Previously, the location was fixed across all computers and so it was easy for the hackers to hack the computer.
There are two software S1 and S2. S1 generates a random number where the heap/library/base of the executable is located. So now, it is difficult for the hacker to predict the location.
Between S1 and S2, both of which have random number generators, which one is better? Can we compare based on the random numbers generated by each software? 

From your application, it seems a uniform distribution might be desirable. If that is the case, you could test the outputs of $S1$ and $S2$ against a uniform distribution using the Kolmogorov-Smirnov test. If one of the algorithms consistently produces lower p-values, discard that and use the other one. 
