In acceptance testing, customer requirements as specified in system specifications have to be tested for their successful implementation. This is a time-consuming task due to inherent system complexity and thus a large number of requirements. In order to reduce efforts in acceptance testing, we introduce a novel approach that exploits redundancies and implicit relations in requirements specifications, which are based on multi-viewpoint techniques, in our case the reference model for open distributed processing (RM-ODP). It deploys requirements clustering and linguistic analysis techniques for reducing the total number of test cases. We report on concrete experiences with this approach within joint R&D work of the Software Quality Lab (s-lab) of the University of Paderborn and HJP Consulting, an international consulting company, specialized in planning, procurement and acceptance testing of national electronic identification (e-ID) systems. The paper is concluded with an overview on the current tool support especially for automated detection of the redundancies and implicit relations in requirements. Also the future work on the tool support for the overall test specification process is discussed.