Predicting Software Bugs Using Web Log Analysis Techniques and Na ve Bayesian Technique

Complexity of a bug helps the development team to plan future software build and releases. This paper introduces an extensive research frame work capable of pre processing web log bug data completely and efficiently. The framework reduces the error rate and improves significant learning performance of the algorithm. This framework helps to investigate the software bug behavior efficiently. For this Na ve Bayesian classifier is applied to predict for the future depending on the current analysis outcomes. Our system is intended to provide for Web Site Maintainers, Web Site Developers, Personalization Systems, Pre-fetched Systems, Recommender Systems and Web Site Analysts as well as software developers to analyze the bugs in the software code.