Enhancing Accuracy of Software Reliability Prediction *

The measurement and prediction of software reliahility require the use of the Software Reliability Growth Models (SRGMs). The predictive quality can be measured by the average end-point projection er-ror L9]. In this paper, the effects of two orthogonal classes of approaches to improve prediction capability of a SRM have been examined using a large number of data sets. The first approach is preprocessing of data to filier out short term noise. The second is to over-come the bias inherent in the model. The results show that proper application of these two approaches can be more important than the selection of the model.