Implementation of Common Genetic and Bacteriological Algorithms in Optimizing Testing Data in Mutation Testing

In this article, at first mutation testing is dealt with. Due to the high costs of mutation testing, it is usually tried to improve testing data by the use of evolutionary algorithms. Genetic algorithms are one of the most commonly used evolutionary algorithms. At first these algorithms are simulated and implemented, and then they are compared with the new bacteriological algorithms, inspired by the growth of the bacteria in nature.