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In recent years, reliability has become a major issue and objective during the design of embedded systems. Here, different techniques to increase reliability like hardware-/software-based redundancy or component hardening are applied systematically during Design Space Exploration (DSE), aiming at achieving highest reliability at lowest possible cost. Existing approaches typically solely provide reliability measures, e.g. failure rate or Mean-Time-To-Failure (MTTF), to the optimization engine, poorly guiding the search which parts of the implementation to change. As a remedy, this work proposes an efficient approach that (a) determines the importance of resources with respect to the system's reliability and (b) employs this knowledge as part of a local search to guide the optimization engine which components/design decisions to investigate. First, we propose a novel approach to derive Importance Measures (IMs …