A Methodology for Automating Assurance Case Generation
This addresses the costly and time-consuming certification processes in domains like automotive and aviation, though it appears incremental as it automates existing practices rather than introducing a new paradigm.
The paper tackles the inefficiency and brittleness of manual safety case generation for cyber-physical systems by introducing an automated tool that constructs and evaluates safety cases using system design artifacts, evidence, and developer expertise, demonstrated on a remote-control car testbed.
Safety Case has become an integral component for safety-certification in various Cyber Physical System domains including automotive, aviation, medical devices, and military. The certification processes for these systems are stringent and require robust safety assurance arguments and substantial evidence backing. Despite the strict requirements, current practices still rely on manual methods that are brittle, do not have a systematic approach or thorough consideration of sound arguments. In addition, stringent certification requirements and ever-increasing system complexity make ad-hoc, manual assurance case generation (ACG) inefficient, time consuming, and expensive. To improve the current state of practice, we introduce a structured ACG tool which uses system design artifacts, accumulated evidence, and developer expertise to construct a safety case and evaluate it in an automated manner. We also illustrate the applicability of the ACG tool on a remote-control car testbed case study.