SOFTWARE RELIABILITY ANALYSIS INCORPORATING SECOND-ORDER ARCHITECTURAL STATISTICS
Swapna S. Gokhale · International Journal of Reliability Quality and Safety Engineering · 2005
Architecture-based techniques for reliability assessment of software applications have received increased attention in the past few years due to the advent of component-based software development paradigm. Most of the prior research efforts in architecture-based analysis use the composite solution approach to solve the architecture-based models in order to estimate application reliability. Though the composite solution approach produces an accurate estimate of application reliability, it suffers from several drawbacks. The most notable drawback of the composite solution approach is that it does not allow an analysis of the sensitivity of the application reliability to the reliabilities of the components comprising the application and the application structure. The hierarchical solution approach on the other hand, has the potential of overcoming the drawbacks of the composite approach. However, in the present form, the hierarchical solution approach produces an estimate of application reliability which is only an approximation of the estimate produced by the composite approach since it does not take into consideration the second-order architectural statistics. Also, although the hierarchical solution approach can be used for sensitivity analysis, mathematical techniques to perform such analysis are lacking. Development of an accurate hierarchical solution approach to estimate application reliability based on its architecture is the focus of this paper. Using the approach described in this paper, an analytical application reliability function which incorporates second-order architectural statistics can be obtained. Sensitivity analysis techniques and expressions to determine the mean time to failure of the application are developed based on this analytical reliability function. We illustrate the reliability prediction, sensitivity analysis, and mean time to failure computation techniques presented in this paper using two case studies.