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On Wikipedia and other sites running on MediaWiki, Special:Random can be used to access a random article in the main namespace; this feature is useful as a tool to generate a random article.
Random number generators are important in many kinds of technical applications, including physics, engineering or mathematical computer studies (e.g., Monte Carlo simulations), cryptography and gambling (on game servers ). This list includes many common types, regardless of quality or applicability to a given use case.
Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated. This means that the particular outcome sequence will contain some patterns detectable in hindsight but impossible to foresee.
In theoretical computer science and cryptography, a pseudorandom generator (PRG) for a class of statistical tests is a deterministic procedure that maps a random seed to a longer pseudorandom string such that no statistical test in
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In computing, a hardware random number generator (HRNG), true random number generator (TRNG), non-deterministic random bit generator (NRBG), or physical random number generator is a device that generates random numbers from a physical process capable of producing entropy (in other words, the device always has access to a physical entropy source ...
A cryptographically secure pseudorandom number generator (CSPRNG) or cryptographic pseudorandom number generator (CPRNG) is a pseudorandom number generator (PRNG) with properties that make it suitable for use in cryptography. It is also referred to as a cryptographic random number generator (CRNG).
Filler text (also placeholder text or dummy text) is text that shares some characteristics of a real written text, but is random or otherwise generated. It may be used to display a sample of fonts, generate text for testing, or to spoof an e-mail spam filter.
Non-uniform random variate generation or pseudo-random number sampling is the numerical practice of generating pseudo-random numbers (PRN) that follow a given probability distribution. Methods are typically based on the availability of a uniformly distributed PRN generator.
Disposable email addressing sets up a different, unique email address for every sender or recipient combination. The method is useful in scenarios where someone may sell or release an individual's email address to spam lists or other unethical entities.