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  2. Random seed - Wikipedia

    en.wikipedia.org/wiki/Random_seed

    A random seed (or seed state, or just seed) is a number (or vector) used to initialize a pseudorandom number generator.. A pseudorandom number generator's number sequence is completely determined by the seed: thus, if a pseudorandom number generator is later reinitialized with the same seed, it will produce the same sequence of numbers.

  3. /dev/random - Wikipedia

    en.wikipedia.org/wiki/Dev/random

    The /dev/urandom device typically was never a blocking device, even if the pseudorandom number generator seed was not fully initialized with entropy since boot. Not all operating systems implement the same methods for /dev/random and /dev/urandom. This special file originated in Linux in 1994. It was quickly adopted by other Unix-like operating ...

  4. Lazarus (software) - Wikipedia

    en.wikipedia.org/wiki/Lazarus_(software)

    ASuite is a free open-source application launcher for Windows. From 2.1 Alpha 1, it's fully written in Lazarus/FPC. Beyond Compare is a data comparison utility for Windows, macOS, and Linux. The macOS and Linux versions are compiled using Lazarus/FPC. Cartes du Ciel is a free planetarium program for Linux, macOS and Windows. The software maps ...

  5. Pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_number_generator

    The PRNG-generated sequence is not truly random, because it is completely determined by an initial value, called the PRNG's seed (which may include truly random values). Although sequences that are closer to truly random can be generated using hardware random number generators , pseudorandom number generators are important in practice for their ...

  6. Randomness extractor - Wikipedia

    en.wikipedia.org/wiki/Randomness_extractor

    Intuitively, an extractor takes a weakly random n-bit input and a short, uniformly random seed and produces an m-bit output that looks uniformly random. The aim is to have a low d {\displaystyle d} (i.e. to use as little uniform randomness as possible) and as high an m {\displaystyle m} as possible (i.e. to get out as many close-to-random bits ...

  7. Pseudorandomness - Wikipedia

    en.wikipedia.org/wiki/Pseudorandomness

    In many applications, the deterministic process is a computer algorithm called a pseudorandom number generator, which must first be provided with a number called a random seed. Since the same seed will yield the same sequence every time, it is important that the seed be well chosen and kept hidden, especially in security applications, where the ...

  8. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    CPython is distributed with a large standard library written in a mixture of C and native Python, and is available for many platforms, including Windows (starting with Python 3.9, the Python installer deliberately fails to install on Windows 7 and 8; [141] [142] Windows XP was supported until Python 3.5) and most modern Unix-like systems ...

  9. Pseudorandom generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_generator

    If a full derandomization is desired, a completely deterministic simulation proceeds by replacing the random input to the randomized algorithm with the pseudorandom string produced by the pseudorandom generator. The simulation does this for all possible seeds and averages the output of the various runs of the randomized algorithm in a suitable way.