The Automatic Test Data Generation Based Genetic Ant Colony Algorithm

With the development of software technology and the increasement of software project scale, the effect of software testing becomes more and more important. In testing, the selection of test data is a nodus to structure testing. Whether the errors of programs can be detected or not are directly related to whether the test data is right or not. Although some methods are brought out to automatically generate test data, in the practical application there are no perfect solutions because of their localizations. The test data can be gained only by the experiences. This paper focuses on the method of automatically generate test data using genetic algorithms and ant colony algorithm in testing.At the beginning, this paper introduces the software testing technology and the methods of automatic test data generation. On the software testing technology, we introduce the concepts, classes and introduces the methods of automatic test data generation. And then we pointed out the technology of artificial intelligence will successful in this field, according to the actual condition of this problem. Soon afterwards, this paper has introduced realization step and the basic principle of genetic algorithm and ant colony algorithm respectively, and then analyzed the good and shortcoming of each one. So further according to their property of advantage complementary, decided adopting mix algorithm with raise the performance of algorithm. Catch tightly, author has put forward the frame of automatic test case generation system based on Genetic ant colony algorithm, and focal point have elaborated some specific problems need to solve in realization process:such as coding, the selection of fitness function and the improvement of hereditary operator etc.After having solved these problems, author has given the program that Genetic ant colony algorithm, and with which as core, developed the automatic test case generation tool for the selecting route. Finally, author has introduced the use method of developing tool, and run this tool with an actual route as example, have generated test case for this route successfully. The result has shown: this tool is effective fairly, and basically can generate the test case voluntarily for the selecting route. It still has some problems, therefore author has pointed out focal point and the direction of the research of next step in concluding remarks.