Random Numbers Generator Software
Random number generators are some of the most fascinating pieces of programs in computer science. They have many applications ranging from gambling and simulation to cryptography and information security. Similarly, algorithms related to artificial intelligence and machine learning also require such types of numbers.
Working of Random Numbers Generators
A software-based random numbers generator is not purely random as its output is generated by a deterministic process. There is a special type of algorithm that works on an initial condition and generates an output that seems to be different from the previous outputs. However, there is a pattern and the numbers in each stage can be traced back if the parameters of the algorithm are known. Therefore, due to this non-purely random nature, they are called pseudo-random number generators.
For example, one of the most widely used pseudo-random number generators works on the following principle:
Next Output = (Some constant * Previous Output + Some Constant) MOD (Some Constant), where MOD refers to the modulus division.
Or, x(n+1) = ( c1 * x(n) + c2 ) MOD (c3)
Consider, x(0) = 50, c1 = 23, c2 = 47, c3 = 100
Then, x(1) = (23 * 50 + 47) MOD (100) = 1197 MOD 100 = 97
x(2) = (97 * 23 + 47) MOD (100) = 2278 MOD 100 = 78
We can see that the outputs in different iterations are different from one another. However, they are generated by a deterministic algorithm by making use of an initial condition. These types of algorithms are also called recursive algorithms as the current output is used for the evaluation of the next output. The ‘MOD’ term used in the above expression represents a modular division that outputs the remainder of the division instead of the quotient.
Working of Random Name Generators
At the basic level, the random name generator works with the help of a random number generator. When you insert the name list in the generator, the generator stores the list in a database as entries, and each entry is associated with a key or an identification number. The generator learns the number of entries and prepares a range. Then, it generators a random number between that given range. This number corresponds to a random entry in the list and outputs the random name.
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