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You would normally expect from a random-number-generator that it not only generated random numbers, but that the numbers were uniformly randomly generated.

There are two definitions of uniformly random: discrete uniformly random and continuous uniformly random.

Unless I'm missing something, this should throw a monkey wrench into most any code that tampers with the 96-bit integer part of a decimal but leaves the scale unchanged.

In experimenting I found that the number 0.9999999999999999999999999999m, which has 28 nines, has the maximum number of nines possible before the decimal will round up to 1.0m.

To be honest I don't believe the internal format of the C# decimal works the way many people think.

For this reason at least some of the solutions presented here are possibly invalid or may not work consistently.

You would then expect that the probability of getting a number between 0 and 0.5 is the same as getting a number between 0.5 and 1.There are still some problems with the implementation, since it does take into account that some numbers have multiple representations - but it should be much closer to a uniform distribution than the other implementations.I know this is an old question, but the distribution issue Rasmus Faber described kept bothering me so I came up with the following.So one could argue that the proper distribution is a discrete continuous distribution with each representable number having the same probability.That is basically what Jon Skeet's and John Leidegren's implementation does.

Further experimenting proved the following code sets the variable "Dec" to the value 0.9999999999999999999999999999m: It is from this discovery that I came up with the extensions to the Random class that can be seen in the code below.