Software reliability models: an approach to early reliability prediction

Abstract

Software reliability prediction models are of paramount importance since they provide early identification of cost overruns, software development process issues, optimal development strategies, etc. Existing prediction models were developed mostly during the past 5 to 10 years and, hence, have become obsolete. Furthermore, they are not based on a deep knowledge and understanding of the software development process. This limits their predictive power. This paper presents an approach to the prediction of software reliability based on a systematic identification of software process failure modes and their likelihoods. A direct consequence of the approach and its supporting data collection efforts is the identification of weak areas in the software development process. A Bayesian framework for the quantification of software process failure mode probabilities is recommended since it allows usage of historical data that are only partially relevant to the software at hand. The approach is applied to the requirements analysis phase.