Model-Based Testing of Self-Driving Cars

Self-driving cars pose challenges to testing. The quantity and magnitude of sensor inputs create an enormous test vector space. Traditional manual testing methods are inadequate to cover this multi-dimensional vector space with test cases. To address this challenge model-based techniques are applied to manage the testing complexity. Abstraction and automation increase the productivity of test
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