{'fraction_non_alphanumeric': 0.010517090271691499, 'fraction_numerical': 0.0, 'mean_word_length': 5.451977401129944, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
On the Industrial Application of Combinatorial Testing for Autonomous Driving Functions

The growing importance of automated and autonomous driving systems becomes more and more visible in the industrial domain as well as in research. Validation and verification of autonomous driving functions is one of the grand challenges in autonomous vehicle development. Virtual validation using simulation has been widely discussed and proposed as a method to solve the challenge. Furthermore, scenario-based approaches have been considered as proper methods combined with virtual validation in order to identify critical scenarios. In this paper, we discuss a method for testing automated and autonomous driving functions using ontologies and combinatorial testing that is able to automate test case generation. Moreover, we report on the application of the method at the industrial level. There we depict the comprehensive application process from the construction of the ontology to test suite execution in detail. This case study shows that the proposed approach can be used for testing and validation of autonomous driving functions in practice.