Abstract
The paper considers various methods for assessing the quality of pseudorandom number generators. We present visual methods for detecting anomalies, patterns, and deviations in pseudorandom sequences and define quality criteria for the presented methods. Also, we presented results of PRNG research by the proposed methods and proofs of the described methods correctness. Finally, we formulated recommendations to increase the effectiveness of the presented in research methods.
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