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The aim of our work is to provide a modeling framework for evaluating performability measures of Multipurpose, Multiprocessor Systems (MMSs). The originality of our approach is in the explicit separation between the architectural and environmental concerns of a system. The overall dependability model, based on stochastic reward nets, is composed of 1) an architectural model describing the behavior of system hardware and software components, 2) a service-level model, and 3) a maintenance policy model. The two latter models are related to the system utilization environment. The results can be used for supporting the manufacturer design choices as well as the potential end-user configuration selection. We illustrate the approach on a particular family of MMSs under investigation by a system manufacturer for Internet and e-commerce applications. As the systems are scalable, we consider two architectures: a reference one composed of 16 processors and an extended one with 20 processors. Then, we use the obtained results to evaluate the performability of a clustered system composed of four reference systems. We evaluate comprehensive measures defined with respect to the end-user service requirements and specific measures in relation to the distributed shared memory paradigm.