Performance validation tools for software/hardware systems

It is common for software/hardware systems to be fully designed and functionally tested before an attempt is made to verify performance characteristics. Unsatisfactory performance, when discovered late in a system’s development, can cause a costly redesign and implementation of software or hardware and is likely to result in late system delivery. The goal of system performance validation is to provide assurance that a system as a whole is likely to meet its quantitative goals before the system is complete. It exploits performance engineering methods and tools to systematically construct and evaluate predictive system models. The tools must correctly predict system performance at some useful abstraction. This paper compares layered queueing models (LQMs) and stochastic process algebras (SPAs) and their support for system performance validation. In particular, we focus on abstraction and level detail within models and automated model building.