Software reliability engineering: an evolutionary neural network approach
Robert Hochman · 1998
Author: Robert Hochman Title: Software Reliability Engineering: An Evolutionary Neural Network Approach Institution: Florida Atlantic University Thesis Advisor: Dr. Taghi M. Khoshgoftaar Degree: Master of Science Year: 1997 This thesis presents the results of an empirical investigation of the applicability of genetic algorithms to a real--world problem in software reliability --- the fault--prone module identification problem. The solution developed is an effective hybrid of genetic algorithms and neural networks. This approach (ENNs) was found to be superior, in terms of time, effort, and confidence in the optimality of results, to the common practice of searching manually for the best--performing net. Comparisons were made to discriminant analysis. On fault--prone, not--fault--prone, and overall classification, the lower error proportions for ENNs were found to be statistically significant. The robustness of ENNs follows from their superior performance over many data configurations. ...