Retrieved from ” https: Basic tools for plotting vectors of points produced by generators are provided as well. I’m going to assume you don’t want to do a full install of TestU01 as a general library on your system, you just want to use it briefly, so we’ll do a quick and easy temporary install. Brown , Yoko Nagaya. 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.


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Since it also completes almost instantly we do include it in the TestU01 runs that we do. These tests can be applied to the generators predefined in the library and tfstu01 user-defined generators.

TestU01 results

By using this site, you agree to the Terms of Use and Privacy Policy. BarkerJohn Kelsey. Testing the tests is just as important as testing the data if we are to have any confidence in the results that they report to us, which is part of what we’d like to demonstrate here too. The library implements several types of random number generators, including some proposed in the literature and some found in widely used software.

TestU A C library for empirical testing of random number generators – Semantic Scholar

It’s a little more finicky, but quite doable. By capturing the stream of bits as it was read for that test we can subject exactly the same GB of data to other testing to see if might identify anything suspicious which Dieharder had missed. Random numbers in that interval are created from our raw bitstream by taking non-overlapping blocks of 32 bits as an unsigned integer and dividing them by 2 32 to return a double precision floating point value.


Conclusion Using a random-number test suite isn’t hard.

TestU01 – Wikipedia

All of these tests were run on the same set of samples which were read directly from the BitBabbler White devices during this test run with Dieharder. A random stream of bits is expected to have results that go right out to the very edges of probability, but as always, more testing yestu01 warranted to determine if that was just a pure chance result, or if it is a sign of some systemic bias in the output. From those nine tests it produces 17 statistics.

Now it’s the turn of the venerable TestU Predefined tests suites for sequences of uniform random numbers over the interval 0, 1 and for bit sequences are available.


None of which it flagged as being outside of its significance thresholds on this data, though a couple are trstu01 the neighbourhood of them. Testing bit generators with TestU01 is a bit of a pain, because we can only test 32 bits at a time.

Basic tools for plotting vectors of points produced by generators are provided as well. We’ll address these issues in the next examples.

References Publications referenced by this paper. For a more complex RNG, all these times increase by a factor of two or more. This causes it to be more sensitive to flaws in the most-significant bits than the least tesfu01 bits.

The inability to modify the test parameters or add new tests led to the development of the TestU01 library. 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.


Less than six seconds of testing, and we see that unimproved XorShift generators have problems. This technique can be used to determine how large the sample size should be, as a function of the generator’s period length, before the generator starts to fail the test systematically.


It runs 26 separate tests to produce 40 statistics on the data. 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. Writing a Test Program to test Xorshift The TestU01 documentation explains how to test a simple bit generator, and gives sample code. To submit a bug or a comment, send an e-mail to: Skip to search form Skip to main content.

There is some overlap with the Alphabit battery for the type of tests that are run, but most of them are run with different parameters though some of them do have less statistical power when a large number of bits are available, because of it limiting the maximum number of them that it will test in this battery. It configures in the traditional way for Unix software.

AgarwalRobert F. Big Crush takes about 4 hours.