Abstract
An advanced genetic algorithm is proposed to apply to test data generation for paths coverage. We advanced the classical genetic algorithm: divided the population into “families”, using the family-in-crossover in each family and PSO-crossover operator between two families which commixed the thought of particle swarm; Then, the fitness function is designed by consider of the difference degree and the degree of approximation, and the model of the advanced genetic algorithm applying to test data generation for paths coverage is given in detail. Finally, the proposed algorithm is applied to a benchmark program, and compared with previous algorithms; the results show that the proposed algorithm is obviously advantageous in the number of generations and time consumption.
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