Reliability prediction and sensitivity analysis based on software architecture

Prevalent approaches to characterize the behavior of monolithic applications are inappropriate to model modern software systems which are heterogeneous, and are built using a combination of components picked off the shelf, those developed in-house and those developed contractually. Development of techniques to characterize the behavior of such component-based software systems based on their architecture is then absolutely essential. Earlier efforts in the area of architecture-based analysis have focused on the development of composite models which are quite cumbersome due to their inherent largeness and stiffness. In this paper we develop an accurate hierarchical model to predict the performance and reliability of component-based software systems based on their architecture. This model accounts for the variance of the number of visits to each module, and thus provides predictions closer to those provided by a composite model. The approach developed in this paper enables the identification of performance and reliability bottlenecks. We also develop expressions to analyze the sensitivity of the performance and reliability predictions to the changes in the parameters of individual modules. In addition, we demonstrate how the hierarchical model could be used to assess the impact of changes in the workload on the performance and reliability of the application. We illustrate the performance and reliability prediction as well as sensitivity analysis techniques with examples.

Duke Scholars

Author Kishor S. Trivedi Electrical and Computer Engineering