In embedded systems, safety and reliability are usually important quality characteristics. It is required to determine these properties including hardware and software. Many techniques have been proposed to analyze, model and predict software and hardware quality characteristics on a quantified basis, e.g. fault trees, Markov analysis, and statistical reliability models. It is usually not possible to obtain comprehensive results for real systems by using a single technique. It is thus necessary to apply appropriate techniques to the various parts of a system, and to integrate the techniques or to combine the results in order to obtain a comprehensive result. This requires integrated tools, that share a common database, and offer a variety of modeling techniques - a safety and reliability workbench. We develop the comprehensive safety and reliability workbench ARGOS, that already contains a variety of tools, e.g., a sophisticated fault tree tool (UWG 3.1), automated fault tree generators, e.g., for electronic circuits, software source code, and a software design evaluation and optimization tool (BALANCE), and a statistical reliability analyzer (RAT+). Detailed safety and reliability models of real systems may be very large. It is thus necessary to use modularization and abstraction mechanisms as well as efficient algorithms and representations.