Study On Test Case Optimization Techniques Based On Genetic Algorithms

Once we find faults in software testing, corresponding repairs should be done immediately. Then using regression testing to make sure that old faults are mended and new faults do not brought in. Because of the increasing of size of software, if all test cases are executed, the cost of regression testing can be very high. To reduce cost and improve efficiency, test case optimizing techniques are presented, which goals are to use least test cases to satisfy the test aim. The ways to achieve test case optimize technique are test cases selection, test cases reduction and test cases prioritization. In a word, it's significant to investigate the test case optimize technique.Genetic algorithm, which applies the crossover, mutation and recombine of genes to the problem resolution, is an optimizing approach, imitating the inheritance and evolution in biology. At present genetic algorithm has been brought into test case optimize technique gradually.Be dead against test case prioritization, this paper improve the old evaluation method. The improved evaluation method can make up defect of the old one which ignore one fault can be found by different test cases. On the base of improved evaluation method, a test case prioritization technique based on genetic algorithms be brought out, which can ordering test case according to the goal. The experimental results show that this approach is feasible and effective.