传统软件测试方法中,由于各种实验参数设置没有准确依据数学理论,涉及到的软件测试算法都存在效率偏低的问题,为此,提出基于大数据信息改进的软件测试方法,首先在大数据的背景下,对测试软件目的展开分析,将人的智慧与机器相互结合,通过对社会群体认知与数据价值提炼,使数据从机器智能分析到人类与机器智慧结合的转变;然后对大数据信息软件的三种测试方法进行探讨,第一种是利用粒子群为主线的优化算法,引入蚁群算法作为大数据信息处理机制,可以有效处理大数据信息;第二种就是针对软件特点,提出基于大数据信息处理模型的软件测试方法,通过模型对输人数据进行计算并得出结果;第三种采用仿真原理对软件进行测试;实验结果证明,基于大数据信息软件改进的测试方法不仅可以有效处理数据,还可以提高数据测试效率和软件定位,为今后的软件测试提供有力依据.%the traditional software testing method for a variety of experimental parameter Settings are not accurate according to the mathematical theory,and involves all exist the problem of low efficiency of software testing algorithm.To do this,I put forward a kind of software testing method based on large data information,first of all,under the background of big data,analyzes the purpose of the software of the test,the application of the wisdom of men and machines together,through the understanding of the social group and the value of the data extract,can make the data from the machine's intelligent analysis to the combination of human and machine intelligence.Then three test methods for large data information software were discussed,the first is using particle swarm optimization algorithm as the main line,the introduction of ant colony algorithm as the big data information processing mechanism,can be effective way to deal with large data informatiom;The second is according to the characteristics of the software,and puts forward the software testing method based on large data information processing model,through the model of input data is calculated and the results;The third method USES the principle of simulation to test software.Finally,the experimental results show that based on the large data information software testing method not only can effectively process the data,also can improve the test efficiency of the data and software localization problem,for the future of software testing provides a strong theoretical basis.
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