Predicting Software Bugs Using Web Log Analysis Techniques and Naïve Bayesian Technique

International Journal of Computer Trends and Technology (IJCTT)          
© - Issue 2012 by IJCTT Journal
Volume-3 Issue-1                           
Year of Publication : 2012
Authors :D.Padmabhushana, D.Srikanth.


D.Padmabhushana, D.Srikanth."Predicting Software Bugs Using Web Log Analysis Techniques and Naïve Bayesian Technique"International Journal of Computer Trends and Technology (IJCTT),V3(1):180-186 Issue 2012 .ISSN Published by Seventh Sense Research Group.

Abstract: - Data mining can be applied on bug repositories to explore useful interesting patterns. 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 Naïve 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.


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Keywords — Web server log, Web usage mining, Data mining, User access patterns.