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  2. Fisher–Yates shuffle - Wikipedia

    en.wikipedia.org/wiki/Fisher–Yates_shuffle

    Fisher–Yates shuffle. The Fisher–Yates shuffle is an algorithm for shuffling a finite sequence. The algorithm takes a list of all the elements of the sequence, and continually determines the next element in the shuffled sequence by randomly drawing an element from the list until no elements remain. [1] The algorithm produces an unbiased ...

  3. Random password generator - Wikipedia

    en.wikipedia.org/wiki/Random_password_generator

    The function log 2 is the base-2 logarithm. H is typically measured in bits. [2] [3] Any password generator is limited by the state space of the pseudo-random number generator used if it is based on one. Thus a password generated using a 32-bit generator is limited to 32 bits entropy, regardless of the number of characters the password contains.

  4. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. 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.

  5. JSFuck - Wikipedia

    en.wikipedia.org/wiki/JSFuck

    Other tricks are needed to produce other letters – for example by casting the string 1e1000 into a number, which gives Infinity, which in turn makes the letter y accessible. [ 13 ] The following is a list of primitive values used as building blocks to produce the most simple letters.

  6. Mersenne Twister - Wikipedia

    en.wikipedia.org/wiki/Mersenne_Twister

    The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by Makoto Matsumoto (松本 眞) and Takuji Nishimura (西村 拓士). [1][2] Its name derives from the choice of a Mersenne prime as its period length. The Mersenne Twister was designed specifically to rectify most of the flaws found in older PRNGs.

  7. Applications of randomness - Wikipedia

    en.wikipedia.org/wiki/Applications_of_randomness

    Randomness has many uses in science, art, statistics, cryptography, gaming, gambling, and other fields. For example, random assignment in randomized controlled trials helps scientists to test hypotheses, and random numbers or pseudorandom numbers help video games such as video poker. These uses have different levels of requirements, which leads ...

  8. Pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_number_generator

    A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG), [1] is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by an initial value, called ...

  9. Hardware random number generator - Wikipedia

    en.wikipedia.org/wiki/Hardware_random_number...

    A USB-pluggable hardware true random number generator. In computing, a hardware random number generator (HRNG), true random number generator (TRNG), non-deterministic random bit generator (NRBG), [1] or physical random number generator [2] [3] 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 ...