Performance prediction for industrial software with the APPEAR method

The Analysis and Prediction of Performance for Evolving Architectures (APPEAR) method aims at the performance estimation of newly developed or adapted parts of software product families during the architecting phase. Early performance prediction allows checking the feasibility of systems before their implementation and thus saves money and effort from developing potentially infeasible products. In contrast to all the existing methods, it combines both structural and statistical techniques. It allows choosing which part of the application is structurally modeled, and which part is statistically approximated. The statistical approach is employed to model those parts of a system that remain unchanged for a long time during the evolution. The analytical approach is used to model the parts of the system that evolve rapidly and that are thus not yet implemented. Also here, statistical modeling helps to abstract from internal details of components and thus to reduce the modeling complexity. Often, a simulation model can be built that provides fast feedback on the changes of relevant parts. The method was checked using case studies in the Consumer Electronics and the Medical Imaging System domains. The initial results are encouraging for the case of single components. The APPEAR method is currently being extended to address performance prediction for component compositions