Test Input Partitioning For Automated Testing Of Satellite On-Board Image Processing Algorithms

On-board image processing technologies in the satellite domain are subject to extremely strict requirements with respect to reliability and accuracy in hard real-time. Due to their large input domain, it is infeasible to execute all possible test cases. To overcome this problem, we define a novel test approach that efficiently and systematically captures the input domain of satellite on-board image processing applications. To achieve this, we first present a dedicated partitioning into equivalence classes for each input parameter. Then, we define multidimensional coverage criteria to assess a given test suite for its coverage on the complete input domain. Finally, we present a test generation algorithm that automatically inserts missing test cases into a given test suite based on our multidimensional coverage criteria. This results in a reasonably small test suite that covers the whole input domain of satellite on-board image processing applications. We demonstrate the effectiveness of our approach with experimental results from the ESA medium-class mission PLATO.