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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 ...
shuf is a command-line utility included in the textutils package of GNU Core Utilities for creating a standard output consisting of random permutations of the input. The version of shuf bundled in GNU coreutils was written by Paul Eggert. It is not a part of POSIX. [1]
For instance, AFL is a dumb mutation-based fuzzer that modifies a seed file by flipping random bits, by substituting random bytes with "interesting" values, and by moving or deleting blocks of data. However, a dumb fuzzer might generate a lower proportion of valid inputs and stress the parser code rather than the main components of a program.
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 ...
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.
This is a list of POSIX (Portable Operating System Interface) commands as specified by IEEE Std 1003.1-2024, which is part of the Single UNIX Specification (SUS). These commands can be found on Unix operating systems and most Unix-like operating systems.
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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.