Cost-Effective Simulation-Based Test Selection in Self-Driving Cars SW

Explore a 42-minute conference talk from Devoxx on cost-effective simulation-based test selection for self-driving car software. Delve into the challenges of testing complex autonomous vehicle systems and learn about SDC-Scissor, a framework that uses machine learning to identify and skip unlikely fault-detecting tests. Discover how this approach can significantly reduce simulation time and increase cost-effectiveness in testing self-driving car software. Gain insights into cyberphysical systems, mobility reliability, and real-world use cases of anomalies in self-driving cars. Understand the importance of proper testing methodologies and how they contribute to enhancing the safety of autonomous vehicles. Find out more about the SDCC tool, test prioritization, and ongoing research in this critical field of automotive technology.