Equivalence class definition for automated testing of satellite on-board image processing

Abstract

On-board image processing technologies in the satellite domain are subject to strict requirements with respect to reliability and accuracy in hard real-time. Due to the large input domain of such processing technologies it is impracticable or even impossible to execute all possible test cases. As a solution we define a novel test approach that efficiently and systematically captures the input domain of satellite on-board image processing applications. We first partition each input parameter into equivalence classes. Based on these equivalence classes we define multidimensional coverage criteria to assess the coverage of a given test suite on the whole input domain. Finally, our test generation algorithm automatically inserts missing but relevant test cases into the given test suite such that our multidimensional coverage criteria are satisfied. As a result we get a reasonably small test suite that covers the complete input domain. We demonstrate the effectiveness of our approach with experimental results from the ESA medium-class mission PLATO.