How to resolve the algorithm Random number generator (included) step by step in the Nanoquery programming language
Published on 12 May 2024 09:40 PM
How to resolve the algorithm Random number generator (included) step by step in the Nanoquery programming language
Table of Contents
Problem Statement
The task is to: Note: the task is not to create an RNG, but to report on the languages in-built RNG that would be the most likely RNG used. The main types of pseudo-random number generator (PRNG) that are in use are the Linear Congruential Generator (LCG), and the Generalized Feedback Shift Register (GFSR), (of which the Mersenne twister generator is a subclass). The last main type is where the output of one of the previous ones (typically a Mersenne twister) is fed through a cryptographic hash function to maximize unpredictability of individual bits. Note that neither LCGs nor GFSRs should be used for the most demanding applications (cryptography) without additional steps.
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Source code in the nanoquery programming language
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