How is a random number generated at runtime?

Question

Since computers cannot pick random numbers(can they?) how is this random number actually generated. For example in C# we say,

Random.Next()

Answer 1

I don't know much details but what I know is that a seed is used in order to generate the random numbers it is then based on some algorithm that uses that seed that a new number is obtained.

If you get random numbers based on the same seed they will be the same often.

Answer 2

Since computers cannot pick random numbers (can they?)

As others have noted, "Random" is actually pseudo-random. To answer your parenthetical question: yes, computers can pick truly random numbers. Doing so is much more expensive than the simple integer arithmetic of a pseudo-random number generator, and usually not required. However there are applications where you must have non-predictable true randomness: cryptography and online poker immediately come to mind. If either use a predictable source of pseudo-randomness then attackers can decrypt/forge messages much more easily, and cheaters can figure out who has what in their hands.

The .NET crypto classes have methods that give random numbers suitable for cryptography or games where money is on the line. As for how they work: the literature on crypto-strength randomness is extensive; consult any good university undergrad textbook on cryptography for details.

Specialty hardware also exists to get random bits. If you need random numbers that are drawn from atmospheric noise, see www.random.org.

Answer 3

I'll just add an answer to the first part of the question (the "can they?" part).h

Computers can generate (well, generate may not be an entirely accurate word) random numbers (as in, not pseudo-random). Specifically, by using environmental randomness which is gotten through specialized hardware devices (that generates randomness based on noise, for e.g.) or by using environmental inputs (e.g. hard disk timings, user input event timings).

However, that has no bearing on the second question (which was how Random.Next() works).

Answer 4

You may checkout this article. According to the documentation the specific implementation used in .NET is based on Donald E. Knuth's subtractive random number generator algorithm. For more information, see D. E. Knuth. "The Art of Computer Programming, volume 2: Seminumerical Algorithms". Addison-Wesley, Reading, MA, second edition, 1981.

Answer 5

The Random class is a pseudo-random number generator.

It is basically an extremely long but deterministic repeating sequence. The "randomness" comes from starting at different positions. Specifying where to start is done by choosing a seed for the random number generator and can for example be done by using the system time or by getting a random seed from another random source. The default Random constructor uses the system time as a seed.

The actual algorithm used to generate the sequence of numbers is documented in MSDN:

The current implementation of the Random class is based on Donald E. Knuth's subtractive random number generator algorithm. For more information, see D. E. Knuth. "The Art of Computer Programming, volume 2: Seminumerical Algorithms". Addison-Wesley, Reading, MA, second edition, 1981.

Answer 6

Computers use pseudorandom number generators. Essentially, they work by start with a seed number and iterating it through an algorithm each time a new pseudorandom number is required.

The process is of course entirely deterministic, so a given seed will generate exactly the same sequence of numbers every time it is used, but the numbers generated form a statistically uniform distribution (approximately), and this is fine, since in most scenarios all you need is stochastic randomness.

The usual practice is to use the current system time as a seed, though if more security is required, "entropy" may be gathered from a physical source such as disk latency in order to generate a seed that is more difficult to predict. In this case, you'd also want to use a cryptographically strong random number generator such as this.