Predicting Software Bugs Using Web Log Analysis Techniques and Na?ve Bayesian Technique
With the continued growth and proliferation of Web services, software as a services and Web based information systems, the volumes of user data have reached astronomical proportions. As the World Wide Web is continuously and rapidly growing, it is necessary for the web miners to utilize intelligent tools in order to find, extract, filter and evaluate the bugs information. The data preprocessing stage is the most important phase for investigation of the web bugs behavior. To do this one must extract the only human user accesses from weblog data which is critical and complex.