Abstract. Matlab/Simulink is a widely used modeling notation for control systems design in automotive industries. Safety standards, such as ISO 26262, are emphasizing model-based testing, in which, test cases derived from the design model are used to show model-code conformance. In this paper, we propose a new aspect-oriented test case generation approach called "MB-ATG" from Simulink models. This approach exploits model checking technique capability to generate counterexamples that constitute test cases. We experiment a real automotive Simulink model with MB-ATG prototype to show its performance. Experimental results show that MB-ATG approach is compliant with standard structural coverage criteria and does not provide redundant test cases.
Safety standards, such as ISO 2626-2, are empha sizing model based testing to argue the compliance between a model and its implementation. Model based testing has de fined structural and behavioral coverage criteria to derive test cases. Both model and its relative implementation generate their respective results after processing test cases. If these results are different, a compliance problem will be thrown. TELNET Innovation Labs has modeling control systems in automotive and aerospace solutions with SimulinkiStateflow (SL/SF) and has tested them using a semi-automatic process. We propose a tool to generate test cases from Simulink models using SLDV (Simulink Design Verifier) model checker. We compare our tool performance to the TELNET Innovaltion Labs testing process and two other prominent commercial tools, such as Sal-ATG and Simulink test case generator.
Safety-critical applications require complete high-coverage testing, which is not always guaranteed by model-based test generation techniques. Recently, automatic test generation by model checking has been reported to improve the efficiency of test suites over conventional test generation techniques. This study introduces our novel tool SimAutoGen, which employs the model checking technique (as a formal verification technique) to derive test vectors from Simulink models of automotive controllers according to structural coverage metrics. Model checking based on test generation is challenging for two reasons. First, the input model to the model checker requires conversion into a formal language. Second, standard tools have limited ability to generate test vectors for large-scale Simulink models because the state-space explodes with increasing model size. Our proposed SimAutoGen avoids the first problem by expressing the properties to be verified, which correspond to a structural coverage metric, in the Simulink language. To solve the state-space explosion problem, we developed a new algorithm that slices the Simulink model into hierarchical levels. This research and innovation work is conducted within a MOBIDOC thesis funded by the European Union under the PASRI project. This work is a collaboration between TELNET Innovation Labs and computer science and industrial systems laboratory.
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