TestU01: A C library for empirical testing of random number generators

@article{LEcuyer2007TestU01AC,
  title={TestU01: A C library for empirical testing of random number generators},
  author={Pierre L'Ecuyer and Richard J. Simard},
  journal={ACM Trans. Math. Softw.},
  year={2007},
  volume={33},
  pages={22:1-22:40}
}
We introduce TestU01, 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 (RNGs). It provides general implementations of the classical statistical tests for RNGs, as well as several others tests proposed in the literature, and some original ones. Predefined tests suites for sequences of uniform random numbers over the interval (0, 1) and for bit sequences are available. Tools are… Expand
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References

SHOWING 1-10 OF 207 REFERENCES
Sparse Serial Tests of Uniformity for Random Number Generators
TLDR
For the classes of alternatives that correspond to linear generators, the most efficient tests turn out to have $k \gg n$ (in contrast to what is usually done or recommended in simulation books) and to use overlapping vectors. Expand
A random number generator for PC's
Abstract It is now possible to do serious scientific work on personal computers (PC's). Many simulation studies, whether exploratory or for production runs, call for random numbers. We offer here aExpand
Some Difficult-to-pass Tests of Randomness
We describe three tests of randomness-- tests that many random number generators fail. In particular, all congruential generators-- even those based on a prime modulus-- fail at least one of theExpand
A universal statistical test for random bit generators
  • U. Maurer
  • Mathematics, Computer Science
  • Journal of Cryptology
  • 2004
TLDR
A new statistical test for random bit generators is presented which can detect any significant deviation of a device's output statistics from the statistics of a truly random bit source when the device can be modeled as an ergodic stationary source with finite memory but arbitrary (unknown) state transition probabilities. Expand
A Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications
Abstract : This paper discusses some aspects of selecting and testing random and pseudorandom number generators. The outputs of such generators may he used in many cryptographic applications, such asExpand
Physical models as tests of randomness.
  • Vattulainen, Ala-Nissila, Kankaala
  • Mathematics, Medicine
  • Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
  • 1995
TLDR
A test bench for random number sequences based on the use of physical models is presented and the cluster test is shown to be particularly eecient in detecting periodic correlations on bit level, while the autocorrelation, the random walk, and the n{block tests are very well suited for studies of weak correlations inrandom number sequences. Expand
The serial test for sampling numbers and other tests for randomness
In the serial test for sampling numbers ( 3, 4 ) an expression is used. It is in the form of a sum of squares and has previously been supposed to have asymptotically a χ 2 (γ-variate) distribution.Expand
Random numbers for simulation
TLDR
This paper focuses mainly on efficient and recently proposed techniques for generating uniform pseudorandom numbers, and aims to design more robust generators without having to pay too much in terms of portability, flexibility, and efficiency. Expand
Random Number Generation for the New Century
Abstract Use of empirical studies based on computer-generated random numbers has become a common practice in the development of statistical methods, particularly when the analytical study of aExpand
Software for uniform random number generation: distinguishing the good and the bad
  • P. L'Ecuyer
  • Computer Science
  • Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304)
  • 2001
TLDR
An object-oriented random number package where random number streams can be created at will, and with convenient tools for manipulating the streams, is presented and is implemented in the Arena and AutoMod simulation tools. Expand
...
1
2
3
4
5
...