System designers need to have insight in the response times of service systems to see if they meet performance requirements. We present a high-level evaluation technique to obtain the distribution of services completion times. It is based on a high-level domain-specific language that hides the underlying technicalities from the system designer. Under the hood, probabilistic real-time model checking technology is used iteratively to obtain precise bounds and probabilities. This allows reasoning about nondeterministic, probabilistic and real-time aspects in a single evaluation. To reduce the state spaces for analysis, we use two sampling methods (for measurements) that simplify the system model: (i) applying an abstraction on time by increasing the length of a (discrete) model time unit, and (ii) computing only absolute bounds by replacing probabilistic choices with non-deterministic ones. We use an industrial case on image processing of an interventional X-ray system to illustrate our approach.

iDSL is a language and toolbox for performance prediction of Medical Imaging Systems; It enables system designers to automatically evaluate the performance of their designs, using advanced means of model checking and simulation techniques under the hood, and presents results graphically. In this paper, we present a performance evaluation approach based on iDSL that (i) relies on few measurements; (ii) evaluates many different design alternatives (so-called "designs"); (iii) provides understandable metrics; and (iv) is applicable to real complex systems. Next to that, iDSL supports advanced methods for model calibration as well as ways to aggregate performance results. An extensive case study on interventional X-ray systems shows that iDSL can be used to study the impact of different hardware platforms and concurrency choices on the overall system performance. Model validation conveys that the predicted results closely reflect reality.

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