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  2. Random test generator - Wikipedia

    en.wikipedia.org/wiki/Random_test_generator

    Random test generators (often abbreviated RTG or ISG [1] for Instruction Stream Generator or Instruction Sequence Generator [1]) are a type of computer software that is used in functional verification of microprocessors. Their primary use lies in providing input stimulus to a device under test.

  3. Randomness test - Wikipedia

    en.wikipedia.org/wiki/Randomness_test

    A randomness test (or test for randomness), in data evaluation, is a test used to analyze the distribution of a set of data to see whether it can be described as random (patternless). In stochastic modeling , as in some computer simulations , the hoped-for randomness of potential input data can be verified, by a formal test for randomness, to ...

  4. Diehard tests - Wikipedia

    en.wikipedia.org/wiki/Diehard_tests

    A random 32×32 binary matrix is formed, each row a 32-bit random integer. The rank is determined. That rank can be from 0 to 32, ranks less than 29 are rare, and their counts are pooled with those for rank 29. Ranks are found for 40000 such random matrices and a chi square test is performed on counts for ranks 32, 31, 30 and ≤ 29.

  5. AI could be used to help generate exam question papers ... - AOL

    www.aol.com/ai-could-used-help-generate...

    Artificial intelligence could be used to help generate exam questions, the head of England’s exams regulator has suggested. Sir Ian Bauckham, interim chief regulator at Ofqual, said artificial ...

  6. Random testing - Wikipedia

    en.wikipedia.org/wiki/Random_testing

    Random testing is a black-box software testing technique where programs are tested by generating random, independent inputs. Results of the output are compared against software specifications to verify that the test output is pass or fail. [ 1 ]

  7. Statistical randomness - Wikipedia

    en.wikipedia.org/wiki/Statistical_randomness

    The first tests for random numbers were published by M.G. Kendall and Bernard Babington Smith in the Journal of the Royal Statistical Society in 1938. [2] They were built on statistical tools such as Pearson's chi-squared test that were developed to distinguish whether experimental phenomena matched their theoretical probabilities.