Java Programming/Random numbers

Random numbers __NOTOC__ To generate random numbers the Math.random() method can be used, which returns a , greater than or equal to 0.0 and less than 1.0. The following code returns a random integer between n and m (where n <= randomNumber < m): Code section 3.30: A random integer. int randomNumber = n + (int)(Math.random() * ( m - n )); Alternatively, the java.util.Random class provides methods for generating random s, s, s, s, s and 'Gaussians' (s from a normal distribution with mean 0.0 and standard deviation 1.0). For example, the following code is equivalent to that above: Code section 3.31: A random integer with Gaussian. Random random = new Random(); int randomNumber = n + random.nextInt(m - n); As an example using random numbers, we can make a program that uses a Random object to simulate flipping a coin 20 times: Code listing 3.25: CoinFlipper.java import java.util.Random; public class CoinFlipper { public static void main(String[] args) { // The number of times to flip the coin final int TIMES_TO_FLIP = 20; int heads = 0; int tails = 0; // Create a Random object Random random = new Random(); for (int i = 0; i < TIMES_TO_FLIP; i++) { // 0 or 1 int result = random.nextInt(2); if (result == 1) { System.out.println("Heads"); heads++; } else { System.out.println("Tails"); tails++; } } System.out.println("There were " + heads + " heads and " + tails + " tails"); } }Possible output for code listing 3.25 Heads Tails Tails Tails Heads Tails Heads Heads Heads Heads Heads Heads Tails Tails Tails Tails Heads Tails Tails Tails There were 9 heads and 11 tails Of course, if you run the program you will probably get different results. Truly random numbers Both Math.random() and the Random class produce pseudorandom numbers. This is good enough for a lot of applications, but remember that it is not truly random. If you want a more secure random number generator, Java provides the java.security.SecureRandom package. What happens with Math.random() and the Random class is that a 'seed' is chosen from which the pseudorandom numbers are generated. SecureRandom increases the security to ensure that the seed which is used by the pseudorandom number generator is non-deterministic — that is, you cannot simply put the machine in the same state to get the same set of results. Once you have created a SecureRandom instance, you can use it in the same way as you can the Random class. If you want truly random numbers, you can get a hardware random number generator or use a randomness generation service. Add some exercises like the ones in Variables 75%