Novel Algorithms for Web Software Fault Prediction

Abstract

Reliability is gaining importance with time for Web system because of the popularity of different Web-based applications, namely, different Web sites and social community networks. In order to aggrandize the reliability of a Web system, some methods are required to measure its current reliability. In recent years, some research works have been carried out on Web software error analysis and reliability predictions. In all these research works, the Web environment has been considered as a crisp one. This is not in reality. Hence, in this paper, a novel clustering algorithm and a multivariate fuzzy logic and fuzzy time series based prediction algorithm for Web software fault prediction have been developed. The proposed prediction algorithm can predict the occurrences of more than one Web error, in a single day, on a single run. Proposed methods have been validated using some real Web failure data extracted from the HTTP logs (access and error logs) of www.ismdhanbad.ac.in (the official Web site of Indian School of Mines Dhanbad, India), which were collected from the Indian School of Mines Web server.