Extracting test cases by using data mining; reducing the cost of testing

In this paper Case-Based Reasoning and Data mining are used as efficient methods for effort estimation and automated testing has been investigated respectively If your software has many outstanding features but does not work properly due to lack of testing, your software is subjected to fail so in order to test them properly, the test results could help the developer to classify them in different categories such as different process models and different types of errors in each developing life cycle phase, then by having these classified results and using data mining methods and Case-Based Reasoning, it would be easy to have the new software's properties and estimate the future test cases in order to reduce the cost of testing phase and eventually the developing cost in similar upcoming projects. In this paper we try to emphasize on testing the similar software with similar test cases. To make it much more efficient, a case with different types of attributes is designed for each software which shows the behavior of it, then we evaluate any upcoming software by fining the most similar case for it from the stored cases and do the performed test cases for it. By estimating the proper set of domains for each attributes, we could increase the efficiency.