Software testing is an important process for ensuring the quality of the software. As the complexity of the software increases, traditional means of manual testing becomes increasingly more complex and time consuming. In most embedded systems, designing software with as few errors as possible is often critical. Resource usage is also of concern for proper behavior because of the very nature of embedded systems.  To design reliable and energy-efficient systems, methods are needed to detect hot points of consumption and correct them prior to deployment. To reduce testing effort, Model-based testing can be used which is one testing method that allows for automatic testing of model based systems. Model-based testing has not been investigated extensively for revealing resource usage anomalies in embedded systems. UPPAAL SMC is a statistical model checking tool which can be used to model the system’s resource usage. Currently UPPAAL SMC lacks the support for performing automatic test generation and test selection. In this thesis we provide this support with a framework for automatic test generation and test selection using mutation analysis, a method for minimizing the generated test suite while maximizing the fault coverage and a tool implementing the framework on top of the UPPAAL SMC tool. The thesis also evaluates the framework on a Brake by Wire industrial system. Our results show that we could for a Brake-by-wire system, simulated on a consumer processor with five mutants, in best case find a test case that achieved 100% mutation score within one minute and confidently identify at least one test case that achieved full mutation score within five minutes. The evaluation shows that this framework is applicable and relatively efficient on an industrial system for reducing continues resource usage target testing effort.