Performance prediction and measurement approaches for component-based software systems help software architects to evaluate their systems based on component performance specifications created by component developers. Integrating classical performance models such as queueing networks, stochastic Petri nets, or stochastic process algebras, these approaches additionally exploit benefits of component-based software engineering, such as reuse and division of work. Although researchers have proposed many approaches into this direction during the last decade, none of them has attained widespread industrial use. On this behalf, we have conducted a comprehensive state-of-the-art survey of more than 20 of these approaches assessing their applicability. We classified the approaches according to the expressiveness of their component performance modelling languages. Our survey helps practitioners to select an appropriate approach and scientists to identify interesting topics for future research.