A study on test automation of IVN of intelligent vehicle using model-based testing
Kabsu Han, Insick Son, Jeonghun Cho
Abstract
Kabsu Han, Insick Son, Jeonghun Cho
Abstract
To certify complex functionality of intelligent vehicle, functional testing is critical parts of development process. For practical testing, well-defined test suites which have wide test coverage and appropriate number of test cases are mandatory. Model-based testing is a kind of black box testing that test suites are derived from model of SUT and automatically executed by model-based testing tool. Also, test cases can be generated automatically with test sequence generation. For test automation of IVN of intelligent vehicle, several transition-based models and test suites which derived from practical test sequence generation strategy are developed. Also, test reports are generated automatically to analyze test results via IVN testing tool. To model the intelligent front lamp system, MATLAB/Simulink stateflow was used. Test sequence generation using TT (transition tour) can assure test coverage and reduce functional testing time. For actual IVN testing, Vector CANoe which supports IVN simulation and testing of actual bus was used. The test cases of CANoe are derived from the result of TT so that the test suite can assure the test coverage also.
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To certify complex functionality of intelligent vehicle, functional testing is critical parts of development process. For practical testing, well-defined test suites which have wide test coverage and appropriate number of test cases are mandatory. Model-based testing is a kind of black box testing that test suites are derived from model of SUT and automatically executed by model-based testing tool. Also, test cases can be generated automatically with test sequence generation. For test automation of IVN of intelligent vehicle, several transition-based models and test suites which derived from practical test sequence generation strategy are developed. Also, test reports are generated automatically to analyze test results via IVN testing tool. To model the intelligent front lamp system, MATLAB/Simulink stateflow was used. Test sequence generation using TT (transition tour) can assure test coverage and reduce functional testing time. For actual IVN testing, Vector CANoe which supports IVN simulation and testing of actual bus was used. The test cases of CANoe are derived from the result of TT so that the test suite can assure the test coverage also.
Key concepts: Manual testing, Test suite, Keyword-driven testing, Test Management Approach, Model-based testing, System under test, Stateflow, White-box testing