Shedding Light onto Safety Integrity Level and Basic Software Constraints in a Real-World Automotive Application: Case Study with Driverator Framework
For automotive system designers, it highlights underexplored non-functional constraints (SIL, BSW, memory) in cause-effect chains, but the contribution is primarily descriptive and framework-based.
This paper characterizes a real-world automotive application focusing on safety integrity level (SIL) constraints, AUTOSAR basic software impact, and memory requirements, and introduces the Driverator framework for scalable system analysis.
Automotive electronic control units (ECUs) are intricate systems with hundreds of individual functions, numerous software components, and multiple interdependent tasks. A prevalent structural pattern in these systems are so-called cause-effect chains. While significant research efforts have been dedicated to the temporal analysis and optimization of these chains, particularly minimizing data age and function response times, other crucial non-functional properties remain relatively underexplored. In particular, the safety integrity level (SIL) classification substantially influences the system design by determining task colocation strategies. Improper sharing of functions or interweaving tasks with different safety levels can compromise the integrity of critical functions. Additionally, AUTOSAR basic software (BSW) (e.g. OS, runtime environment, communication stacks, or diagnostics) introduces complexity that varies based on task characteristics and SIL categories. Furthermore, memory requirements present another critical challenge, given the diversity of memory architectures and SIL-specific dependencies that strongly constrain task allocations. This paper thoroughly characterizes a real-world automotive application, describing an automotive application based on SIL constraints, the impact of basic software, and memory requirements. In this context, the Driverator configuration framework is introduced for scalable system analysis.