The time-adaptive statistical testing for random number generators
This addresses efficiency issues for developers and users of random number generators, though it appears incremental as it adapts existing test batteries.
The paper tackles the trade-off between the number of statistical tests in a battery for random number generators and the time required to run them, proposing a time-adaptive battery method that reduces computation time while preserving test power.
The problem of constructing effective statistical tests for random number generators (RNG) is considered. Currently, there are hundreds of RNG statistical tests that are often combined into so-called batteries, each containing from a dozen to more than one hundred tests. When a battery test is used, it is applied to a sequence generated by the RNG, and the calculation time is determined by the length of the sequence and the number of tests. Generally speaking, the longer the sequence, the smaller deviations from randomness can be found by a specific test. So, when a battery is applied, on the one hand, the "better" tests are in the battery, the more chances to reject a "bad" RNG. On the other hand, the larger the battery, the less time can be spent on each test and, therefore, the shorter the test sequence. In turn, this reduces the ability to find small deviations from randomness. To reduce this trade-off, we propose an adaptive way to use batteries (and other sets) of tests, which requires less time but, in a certain sense, preserves the power of the original battery. We call this method time-adaptive battery of tests.