Kernel Methods of Software Reliability Prediction
Zhangguo Shen · 2012
The pridiction of future failure data from observed data sets can been transformed into a problem of nolinear regression,and the kernel functions method is very efficient for solving nolinear regression problems.A kernel functions-based generic model adaptive to the characteristic of the given data sets is used for software failure time prediction,and it is applied to learn and recognize the inherent internal temporal property of software failure sequence in order to capture the most current feature hidden inside the software failure behavior.The experimental results based on fourteen real data sets show that the proposed model has better prediction and applicability than that of some other conditional software reliability prediction models.