DEPENDABILITY MODELING OF REAL-TIME SYSTEMS USING STOCHASTIC REWARD NETS

Dependability modeling plays a major role in the design, validation an d maintenance of real-time computing systems. Typical models provide m easures such as mean time to failure., reliability and safety as funct ions of the component failure rates and fault/error coverage probabili ties. ill this paper we propose a modeling technique that allows the c overage to be dependent upon the. local (i.e. embedded at task level) and global (i.e. available at system level) fault/error detection and recovery mechanisms. This approach also ensures important savings in t erms of the simulation time required for deriving the coverage probabi lities. Stochastic reward nets are employed as a unique. dependability modeling framework. For illustrating the usefulness of this technique . we analyze dependability of a railroad control computer.