nistrngg987 1.2.3
NIST Test Suite for Random Number Generators - SAILab - University of Siena
License: BSD 3-Clause
Keywords: NIST Tests RNG Random Number Generator SAILab USiena Siena SP800-22r1a

NistRng
*******

Luca Pasqualini - SAILab - University of Siena
############################################################

This is a *python 3.6* and above implementation of the **NIST Test Suite for Random Number Generators** (RNGs).
The idea behind this work is to make a script oriented object-oriented framework for said tests.
This is born from my research since I required to use the tests inside a python research project and I found existing
implementation to be not well suited to that task without extensive modifications.

The NIST reference paper can be found at `SP800-22r1a <https://nvlpubs.nist.gov/nistpubs/Legacy/SP/nistspecialpublication800-22r1a.pdf>`_.

This work is inspired by the great work of David Johnston (C) 2017, which can be found on `github <https://github.com/dj-on-github/sp800_22_tests>`_.

**Features**

- All the test in the **NIST** paper vectorized and optimized the best I could
- Class structure for each test allowing for easy debug and use, both in script and inside broader applications
- Utility functions to pack the sequence in 8-bits using numpy and to run the tests in multiple ways
- Cache system both at function level and at test level to improve performance
- Built-in measurement of time required to perform each test
- Default Test class and Result class to allow eventual extension to additional tests

**License**

*BSD 3-Clause License*

For additional information check the provided license file.

**How to install**

If you only need to use the framework, just download the pip package *nistrng* and import the package in your scripts:

- pip install nistrng

If you want to improve/modify/extends the framework, or even just try my own simple benchmarks at home, download or clone
the git `repository <https://github.com/InsaneMonster/NistRng>`_. You are welcome to open issues or participate in the project, especially if further optimization is achieved.

**How to use**

For a simple use case, refer to benchmark provided in the `repository <https://github.com/InsaneMonster/NistRng>`_. For advanced use, refer to the built-in documentation
and to the provided source code in the `repository <https://github.com/InsaneMonster/NistRng>`_.

**Current issues**

Currently the slow speed of both the Serial and Approximate Entropy tests is an open issue. Any solution or improvement is
welcome.

**Can I help?**

Yes, of course! This project is very side to me, so any help in reporting issues, fixing bugs, testing functionalities and overall improving it is welcome!

**Changelog**

**v. 1.2.1:**

- Improved safe-guard against eventual NaN values that may arise inside the score calculations
- Added unpack function to return to the original numeric integer value from a 8-bit binary sequence
- Some minor fixes and adjustments

**v. 1.2.2:**

- Fixed SP800_22R1A_BATTERY dictionary which was missing the cumulative sums test
- Fixed missing parenthesis on test_approximate_entropy.py
- Fixed bugs on some tests for very long sequences
- Some minor fixes and adjustments

**v. 1.2.3:**

- Fixed binary matrix rank test (credits to @scrambler-crypto)
- Fixed a frequencies computation bug (w.r.t. tickets) on the linear complexity test