Support Vector Regression for Software Reliability Growth Modeling and Prediction

In this work, we propose to apply support vector regression (SVR) to build software reliability growth model (SRGM). SRGM is an important aspect in software reliability engineering. Software reliability is the probability that a given software will be functioning without failure during a specified period of time in a specified environment. In order to obtain the better performance of SRGM, practical selection of parameter C for SVR is discussed in the experiments. Experimental results with the classical Sys1 and Sys3 SRGM data set show that the performance of the proposed SVR-based SRGM is better than conventional SRGMs and relative good prediction and generalization ability are achieved.

• Type: Conference
• Year: 2005
• Where: ISNN
• Authors: Fei Xing, Ping Guo
• Keywords: ISNN 2005, Software Reliability, Software Reliability Engineering, Software Reliability Growth