An Analytical Approach to Architecture-Based Software Reliability Prediction

Prevalent approaches to software reliability modeling are black-box based, i.e., the the software system is treated as a monolithic entity and only its interactions with the outside world are modeled. However, with the advancement and widespread use of object oriented systems design and web-based development, the use of component-based software development is on the rise. Software systems are being developed in a heterogeneous fashion using components developed in-house, contractually, or picked off-the-shelf, and hence it may be inappropriate to model the overall failure process of such systems using the existing software reliability growth models. Predicting the reliability of a heterogeneous software system based on its architecture, and the failure behavior of its components is thus absolutely essential. In this paper we present an analytical approach to architecture-based software reliability prediction. The novelty of this approach lies in the idea of parameterizing the analytic model of the software using measurements obtained from testing. To facilitate this we use a coverage analysis tool called ATAC (Automatic Test Analyzer in C), which is a part of a Software Understanding and Diagnosis System ( Suds) developed at Bellcore. We demonstrate the methodology by predicting the reliability of an application called as SHARPE (Symbolic Hierarchical Automated Reliability Predictor), which has been used to solve stochastic models of reliability, performance and performability. This work was supported in part by Bellcore as a core project in the Center for Advanced Computing and Communication, and by the National Science Foundation grant number EEC-9714965