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Run-time quality of software, such as availability and throughput, depends on architectural factors and execution environment characteristics (e.g., CPU speed, network latency). Although the specific properties of the underlying execution environment are unknown at design time, the software architecture can be used to assess the inherent impact of the adopted design decisions on run-time quality. However, the design decisions that arise in complex software architectures exhibit non trivial inter-dependences. This paper introduces an approach that discovers the most influential factors, by exploiting the correlation structure of the analyzed metrics via factor analysis of simulation data.
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