Combining requirement mining, software model checking and simulation-based verification for industrial automotive systems

The verification and validation of industrial closed-loop automotive systems still remains a major challenge. The overall goal is to verify properties of the closed-loop combination of control software and physical plant. While current software model-checking techniques can be applied on a software component of the system, the end result is not very useful unless the interactions with the physical plant and other software components are captured. To this end, we present an industrial case study in which we combine requirement mining, software model-checking, and simulation-based verification to find issues in industrial automotive systems. Our methodology combines the the scalability of simulation-based verification of hybrid systems with the effectiveness of software model-checking at the unit level. We presents two case studies: one on a publicly available Abstract Fuel Control System benchmark and another on an actual production SiLS (Software in the Loop Simulator) benchmark. Together these case studies demonstrate the practicality of the proposed methodology.