# Testing and validating pseudo random sequences

The framework operates without regard to existing native applications and relies instead on binary instructions in a native ISA.The framework determines emulation errors at a machine instruction level.To get around that restriction, a pseudo random number generator (PRNG) can be used.A PRNG is an algorithm that takes a seed value and then produces an evenly distributed sequence of numbers that appears random. In fact, if you use the same seed value to start the generator, you will get the exact same sequence, every time. While for statistical simulations it might not matter or it might even be beneficial if you can reproduce the same sequence of "random" numbers, in cryptography it is potentially disastrous.A pseudo random number generator can be used to generate a sequence of numbers that looks random.

The elapsed time between two "ticks" is random and can be used to generate a random number or sequence.

A random code generator generates one or more sequences of native machine instructions and corresponding initial machine states in a pseudo-random fashion.

The native instructions are generated from an entire set of the native ISA.

we discovered what it means for a number or sequence to be random.

We also talked about how important randomness is in our modern world.