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In computer science, a generator is a routine that can be used to control the iteration behaviour of a loop.All generators are also iterators. [1] A generator is very similar to a function that returns an array, in that a generator has parameters, can be called, and generates a sequence of values.
Mask generation functions are deterministic; the octet string output is completely determined by the input octet string. The output of a mask generation function should be pseudorandom, that is, if the seed to the function is unknown, it should be infeasible to distinguish the output from a truly random string. [1]
In the asymptotic setting, a family of deterministic polynomial time computable functions : {,} {,} for some polynomial p, is a pseudorandom number generator (PRNG, or PRG in some references), if it stretches the length of its input (() > for any k), and if its output is computationally indistinguishable from true randomness, i.e. for any probabilistic polynomial time algorithm A, which ...
It is the lexer generator adopted by projects such as PHP, [4] SpamAssassin, [5] Ninja build system [6] and others. Together with the Lemon parser generator, re2c is used in BRL-CAD . [ 7 ] This combination is also used with STEPcode, an implementation of ISO 10303 standard.
A classic example of a problem which a regular grammar cannot handle is the question of whether a given string contains correctly nested parentheses. (This is typically handled by a Chomsky Type 2 grammar, also termed a context-free grammar .)
Fortuna is a cryptographically secure pseudorandom number generator (CS-PRNG) devised by Bruce Schneier and Niels Ferguson and published in 2003. It is named after Fortuna, the Roman goddess of chance. FreeBSD uses Fortuna for /dev/random and /dev/urandom is symbolically linked to it since FreeBSD 11. [1] Apple OSes have switched to Fortuna ...
Random number generation in kernel space was implemented for the first time for Linux [2] in 1994 by Theodore Ts'o. [6] The implementation used secure hashes rather than ciphers, [clarification needed] to avoid cryptography export restrictions that were in place when the generator was originally designed.
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.