Research Of Test Data Generation Based On Hybrid Tabu Annealing Genetic Algorithm

As one of the assurance of software quality,software testing plays a vital role in the software life cycle.Manual testing brings many problems,such as high cost,long time,low efficiency and poor reliability and so on.At the same time,the quality of test data in automated software testing affects the efficiency and effectiveness of the testing directly.Test data generation is a typical problem of software engineering,and the problem of software engineering turn into a search problem can often get relatively good solutionGenetic algorithm has its unique advantages in searching for the optimal solution.Genetic algorithm can be applied to the test data generation problem by encoding the input parameters of the source program to generate the individual,then evoluting the generation by measure the fieness of the individual,finally getting the test date of the target path.However,the input parameters are often more than one,the encoding of each parameter will affect the efficiency of the iterative process,so cascade coding is used in the encoding.On the target path,the branch function is obtained by inserting the branch node into the branching function,which is used to construct the fitness function.And the genetic algorithm has its shortcomings,too fast convergence will often sink into the local optimal solution,the simulated annealing process added to the crossover and mutation operation,can improve the climbing characteristics of the algorithm,which can be better to jump out.Using tabu search can effectively reduce the roundabout search process after mutation operation,which can increase the diversity of the population and accelerate the process of population iteration.Thus optimized tabu annealing genetic hybrid algorithm can be used to genetate the test data.Through the model of hybrid tabu annealing genetic algorithm,the typical triangulation problem is tested by path,and the algorithm is optimized by the single control of parameters in the process of operation.Compared with the traditional genetic algorithm and annealing genetic algorithm,the hybrid algorithm has been greatly improved in the efficiency of test data generation.Compared with the classical test data generation algorithm and the popular research in recent years,the hybrid algorithm has a great advantage in the test data generation efficiency and the iteration number.