Software Reliability Prediction Model Based on Relevance Vector Machine

Abstract

Relevance vector machines have been successfully used in many domains, while their application in software reliability prediction is still quite rare. In this work, we propose to apply support vector regression (SVR) to build software reliability prediction model (RVMSRPM). We also compare the prediction accuracy of software reliability prediction models based on RVM, SVM, ANN and three traditional NHPP models. Experimental results show that our proposed RVM-based software reliability prediction model could achieve a higher prediction accuracy compared with these models.