Software systems, and automotive software in particular, are becoming increasingly configurable to fulfill customer needs. New methods such as product line engineering facilitate the development and enhance the efficiency of such systems. In modern, versatile systems, the number of theoretically possible variants easily exceeds the number of actually built products. This produces two challenges for quality assurance and especially testing. First, the costs of conventional test methods increase substantially with every tested variant. And secondly, it is no longer feasible to build every possible variant for the purpose of testing. Hence, efficient criteria for selecting variants for testing are necessary.
In this contribution, we propose a new test design method that enables systematic sampling of variants from test cases. We present six optimization criteria to enable control of test effort and test quality by sampling variants with different characteristics. This approach is inherently different to conventional design methods, where firstly variants are selected for testing and then test cases are designed for each variant. Finally, we demonstrate and discuss the feasibility of our approach and compare the results to established test methods for multivariable systems.