Early Software Reliability Prediction with Wavelet Networks Models

摘要：

Accurate reliability estimates can be obtained by using software reliability models only in the later phase of software testing. However, for cost effective and timely, management prediction in the early phase is important. Non-homogenerous Poisson process (NHPP) models and Artificial Neural Network (ANN) models are the most important Analytical software reliability growth models. In this paper we study an approach to using past fault-related data with Wavelet Networks model to improve reliability predictions in the early testing phase. A numerical example is shown with both actual and simulated datasets. The analysis with example shows that the proposed approach works effectively in the early phase of software testing.

关键词： Wavelet Networks Models Early Software Reliability Prediction Accurate

作者: Denghua Mei

作者单位: School of Computer Science and Engineering, South China University of Technology, Guangzhou 510640, P.R. China

会议类型: 国际会议

会议名称: The 2007 International Conference on Intelligent Systems and Knowledge Engineering(第二届智能系统与知识工程国际会议)

会议地点: 成都

会议语种:英文

页码: 535-538

在线出版日期: 2007-10-15（万方平台首次上网日期，不代表论文的发表时间）