TestU01

TestU01 is a software library, implemented in the ANSI C language, and offering a collection of utilities for the empirical statistical testing of uniform random number generators. The library implements several types of random number generators in generic form, as well as many specific generators proposed in the literature or found in widely-used software. It provides general implementations of the classical statistical tests for random number generators, as well as several others proposed in the literature, and some original ones. These tests can be applied to the generators predefined in the library and to user-defined generators. Specific tests suites for either sequences of uniform random numbers in [0,1] or bit sequences are also available. Basic tools for plotting vectors of points produced by generators are provided as well. Additional software permits one to perform systematic studies of the interaction between a specific test and the structure of the point sets produced by a given family of random number generators. That is, for a given kind of test and a given class of random number generators, to determine how large should be the sample size of the test, as a function of the generator’s period length, before the generator starts to fail the test systematically.


References in zbMATH (referenced in 124 articles )

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  1. Almaraz Luengo, Elena: A brief and understandable guide to pseudo-random number generators and specific models for security (2022)
  2. Almaraz Luengo, Elena; Leiva Cerna, Marcos Brian; García Villalba, Luis Javier; Hernandez-Castro, Julio: A new approach to analyze the independence of statistical tests of randomness (2022)
  3. Fan, Chunlei; Ding, Qun; Tse, Chi K.: Evaluating the randomness of chaotic binary sequences via a novel period detection algorithm (2022)
  4. Fried, Sela: The restrictiveness of the hazard rate order and the moments of the maximal coordinate of a random vector uniformly distributed on the probability (n)-simplex (2022)
  5. Haramoto, Hiroshi; Matsumoto, Makoto; Saito, Mutsuo: Unveiling patterns in xorshift128+ pseudorandom number generators (2022)
  6. Zhao, Mengdi; Liu, Hongjun: Construction of a nondegenerate 2D chaotic map with application to irreversible parallel key expansion algorithm (2022)
  7. Haramoto, Hiroshi: Study on upper limit of sample size for a two-level test in NIST SP800-22 (2021)
  8. Kaur, Rajwinder; Singh, Butta: A hybrid algorithm for robust image steganography (2021)
  9. Luo, Yuling; Liu, Yunqi; Liu, Junxiu; Tang, Shunbin; Harkin, Jim; Cao, Yi: Counteracting dynamical degradation of a class of digital chaotic systems via unscented Kalman filter and perturbation (2021)
  10. Machicao, Jeaneth; Ngo, Quynh Quang; Molchanov, Vladimir; Linsen, Lars; Bruno, Odemir: A visual analysis method of randomness for classifying and ranking pseudo-random number generators (2021)
  11. Si, Yuanyuan; Liu, Hongjun; Chen, Yuehui: Constructing keyed strong S-Box using an enhanced quadratic map (2021)
  12. Wu, Xinying; Ma, Yuan; Chen, Tianyu; Lv, Na: A distinguisher for RNGs with LFSR post-processing (2021)
  13. Gevorkyan, M. N.; Demidova, A. V.; Korol’kova, A. V.; Kulyabov, D. S.: A practical approach to testing random number generators in computer algebra systems (2020)
  14. Gevorkyan, M. N.; Korolkova, A. V.; Kulyabov, D. S.; Sevast’yanov, L. A.: A modular extension for a computer algebra system (2020)
  15. L’Ecuyer, Pierre; Wambergue, Paul; Bourceret, Erwan: Spectral analysis of the MIXMAX random number generators (2020)
  16. Liu, Hongjun; Kadir, Abdurahman; Xu, Chengbo: Color image encryption with cipher feedback and coupling chaotic map (2020)
  17. Liu, Yu; Qin, Zheng; Liao, Xiaofeng; Wu, Jiahui: A chaotic image encryption scheme based on Hénon-Chebyshev modulation map and genetic operations (2020)
  18. Lorek, Paweł; Łoś, Grzegorz; Gotfryd, Karol; Zagórski, Filip: On testing pseudorandom generators via statistical tests based on the arcsine law (2020)
  19. Rainer, Benjamin; Pilz, Jürgen; Deutschmann, Martin: Assessing the statistical quality of RNGs (2020)
  20. Shikano, Yutaka; Tamura, Kentaro; Raymond, Rudy: Detecting temporal correlation via quantum random number generation (2020)

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