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

  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.},
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
Byte-oriented efficient implementation of the NIST statistical test suite
This work enrols in this direction presenting a performance efficient version of the well known NIST statistical test suite for random and pseudorandom number generators based on a paradigm shift towards byte stream processing mode inside the tests. Expand
Random Structured Test Data Generation for Black-Box Testing
An automatic method for deriving random generators of complex test data based on computable boolean predicates that specify the well-formed values of the data type is developed, which removes the influence of the distribution of the random data generator used for testing, which results in a reliable ranking. Expand
Parallel implementation of the NIST Statistical Test Suite
  • A. Suciu, I. Nagy, K. Marton, I. Pinca
  • Computer Science
  • Proceedings of the 2010 IEEE 6th International Conference on Intelligent Computer Communication and Processing
  • 2010
The results on improving the well known NIST Statistical Test Suite (STS) by introducing parallelism and a paradigm shift towards byte processing delivering a design that is more suitable for today's multicore architectures are presented. Expand
On Statistical Tests for Randomness Included in the NIST SP800-22 Test Suite and Based on the Binomial Distribution
This paper compute the exact non-asymptotic distribution of p-values produced by few of the tests in the NIST SP 800-22 suite, and proposes some computation-friendly approximations that allow us to explain why intensive testing produces false-positives with a probability much higher than the expected one when considering asymptotic distributions. Expand
A Search for Good Pseudo-random Number Generators : Survey and Empirical Studies
To verify the claim of so-called good generators and rank the existing generators based on strong empirical tests in same platforms, the genre of PRNGs developed so far has been explored and classified into three groups -- linear congruential generator based, linear feedback shift register based and cellular automata based. Expand
Checking the Soundness of Statistical Tests for Random Number Generators by Using a Three-Level Test
This work proposes an experimental method for revealing defects in statistical tests by using a three-level test and investigates the NIST test suite and the test batteries in TestU01, which are widely used statistical packages. Expand
Fault Analysis and Evaluation of a True Random Number Generator Embedded in a Processor
This article describes experiments and several standard statistical tools for the testing of true Random Number Generators and presents experimental results obtained through the study of a generator embedded in a processor in order to illustrate the methodology. Expand
A Method to Compute an Appropriate Sample Size of a Two-Level Test for the NIST Test Suite
Statistical testing of pseudorandom number generators (PRNGs) is indispensable for their evaluation. A common difficulty among statistical tests is how we consider the resulting probability valuesExpand
Statistical Randomness Tests of Long Sequences by Dynamic Partitioning
Random numbers have a wide usage in the area of cryptography. In practice, pseudo random number generators are used in place of true random number generators, as regeneration of them may be required.Expand
Generating random numbers and random sequences that are indistinguishable from truly random sequences is an important task for cryptography. To measure the randomness, statistical randomness testsExpand


Sparse Serial Tests of Uniformity for Random Number Generators
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
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
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
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
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