Automated Test Data Generation Based on Improved Adaptive Genetic Algorithm HCGA

An improved algorithm HCGA is proposed here based on the combination of adaptive genetic algorithm and hill climbing method for automated software test data generation.Adaptive crossover operator and mutation operator are designed to enhance the global search capability of genetic algorithm at starting.Afterwards hill climbing method is embedded to enhance the local search capability.Test examples show that it is better than genetic algorithm and can improve the efficiency of automated test data generation.