Simulation testing is considered the supplement to ensure the safety of Autonomous driving (AD) and advanced driving assistance (ADAS's) systems in terms of time and costs. However, it is very difficult and challenging when the simulation results are unexpected. This work presents a simulation-based metamorphic testing (MT) approach to test the ADAS system, implementing the European new car assessment program (Euro NCAP) standards on OpenStreetMap (OSM). We first defined input patterns and relations related to autonomous driving, following the principles of MT. To assess the approach, we executed three tests in two steps at both the design and system levels. Our results show that none of the three (source) tests detected any collisions. However, for follow-up test cases, the ego vehicle failed to apply brakes to avoid a collision when the speed changed. A real-life issue in the system was immediately revealed and confirmed by the development team. We then designed a mechanism and
Since the popularization of social media, news has entered our lives digitally. While news is spreading broader and faster, fake news is becoming an increasingly popular topic. Fake news detection is therefore important in both social media and research areas. With artificial intelligence technology, software engineers have developed a lot of fake news detection systems. One of the biggest challenges for such systems is that they may face the oracle problem, which means that there may not be a way, or it may take too long time, to confirm the correctness of a specific output. Metamorphic Testing has been applied successfully to alleviate the oracle problem in many different areas, including in artificial intelligence. In this paper, we propose several metamorphic relations for fake news detection and report on experiments using metamorphic testing on fake news detection applications.