关键词: 软件测试, 自组织特征映射, 神经网络, 小生境遗传算法, 测试数据自动生成

Abstract: The automatic test data generation for program functions is one of the elementary problems in software functional testing. This paper addresses the problem by presenting a technique of dynamic self-organizing neural networks to automatically generate test data for revealing software faults. The technique consists of two parts: the first one is niche genetic algorithm, which generate a small initial fault test data set in software input domain; the second one is dynamic self-organizing feature map, which can repeatedly generate lots of test data for finding faults by using initial fault test data set. These can provide the developer with fault data information to identify fault patterns or hypothesis in software. The approach is used on a C program which is part of missile launch control system. Experimental results show that the method is more efficient than niche genetic algorithms and random techniques.

Key words: software test, self-organizing feature map, neural network, niche genetic algorithm, automatic test data generation