Biblio

In transient distributed cloud computing environment, software is vulnerable to attack, which leads to software functional completeness, so it is necessary to carry out functional testing. In order to solve the problem of high overhead and high complexity of unsupervised test methods, an intelligent evaluation method for transient analysis software function testing based on active depth learning algorithm is proposed. Firstly, the active deep learning mathematical model of transient analysis software function test is constructed by using association rule mining method, and the correlation dimension characteristics of software function failure are analyzed. Then the reliability of the software is measured by the spectral density distribution method of software functional completeness. The intelligent evaluation model of transient analysis software function testing is established in the transient distributed cloud computing environment, and the function testing and reliability intelligent evaluation are realized. Finally, the performance of the transient analysis software is verified by the simulation experiment. The results show that the accuracy of the software functional integrity positioning is high and the intelligent evaluation of the transient analysis software function testing has a good self-adaptability by using this method to carry out the function test of the transient analysis software. It ensures the safe and reliable operation of the software.