Software testing is one of the most important phases in the software development procedure which ensures the accordance of the software and its description. Testing is mainly a manual task accomplished by the human operators. This results in increasing the cost and time of the software development process. Also, due to the uncertain nature of the human activities, software reliability will be under threat and the probability of having some aspects and parts of the software untested always would be high. Therefore, the more automatic, the more intelligent, and the more reliable testing procedure always would be of interest.  In this paper we introduce a new approach to the software testing automation in web based applications, using Artificial Neural Network (ANN). The applied ANN will be trained by diverse pairs of input/output data provided according to the software functionality, then it attempts to model a testing tool for the software. Next we can use this ANN-based testing tool to evaluate and test the software. We apply the proposed testing scheme on a modified version of a web based university course registration software and show its performance on both error-free and faulty cases.

Automatic software evaluation, en, Web based software, Black box testing, Artificial Neural Networks