Software Testing Using Genetic Algorithms

The purpose of this work is to introduce a collection of techniques that utilize a genetic algorithm in order to generate test data automatically for software testing. Researchers have been proposing a number of various strategies for generating test data for a number of years now. Each of these methods has its own set of disadvantages. The purpose of this work is to introduce a number of test techniques that are based on Genetic Algorithms (GAs) and that will have different parameters that can be used to automate the generation of test data that is based on the internal structure of the program. In order to determine the most appropriate approach for testing, the factors that have been identified are utilized in the process of evaluating the fitness function of the genetic algorithm. The test populations are taken as input by these algorithms, which then proceed to evaluate the test cases for that particular program. The total effectiveness of the genetic algorithm in the realms of search space exploration and exploitation will be improved as a result of this integration, which will also bring about a higher convergence rate.