Quality standards impose increasingly stringent requirements and constraints on quality of service attributes and measures. As a consequence, aspects, phenomena, and behaviors, hitherto approximated or neglected, have to be taken into account in quantitative assessment in order to provide adequate measures satisfying smaller and smaller confidence intervals and tolerances. With specific regards to reliability and availability, this means that interferences and dependencies involving the components of a system can no longer be neglected. Therefore, in order to support such a trend, specific techniques and tools are required to adequately deal with dynamic aspects in reliability and availability assessment.The main goal of this paper is to demonstrate how state–space based techniques can satisfy such a demand. For this purpose some examples of specific dynamic reliability behaviors, such as common cause failure and load sharing, are considered applying state–space based techniques to study the corresponding reliability models. Different repair policies in availability contexts are also explored. Both Markovian and non-Markovian models are studied via phase type expansion and renewal theory in order to adequately represent and evaluate the considered dynamic reliability aspects in case of generally distributed lifetimes and times to repair.