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 2231-2803.www.ijcttjournal.org. 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.
References-
[1] F. Masseglia, P. Poncelet, and M.Teisseire,”Using data mining techniques on Web access logs to dynamically improve Hypertext structure”, 1999.
[2] Gabriek. Web usage mining and discovery of association rules from HTTP server logs.
[3] David A. Grossman, and Ophir Frieder, Information Retrieval: Algorithms and Heuristics (The Information Retrieval Series) (2nd Edition) (Paperback - Dec 20, 2004)
[4] H. Zeng and D. Rine, Sept. 2004, Estimation of software defects fix effort using neural networks. In Proc. of the Annual International Computer Software And Applications Conference (COMPSAC ’04), Hong Kong, IEEE.
[5] G. Canfora and L. Cerulo, April 2006, Supporting change request assignment in open source development. In Proc. of ACM Symposium on Applied Computing, pages 1767– 1772, Dijon, France.
[6] D. C? ubranic´ and G. C. Murphy, 2004, Automatic bug triage using text categorization. In Proc. International Conference on Software Engineering & Knowledge Engineering (SEKE), pages 92– 97.
Keywords — Web server log, Web usage mining, Data mining, User access patterns.