Automated Evidence Analysis of Safety Arguments Using Digital Dependability Identities

Abstract

Creating a sound argumentation of why a system is sufficiently safe is a major part of the assurance process. Today, compiling a safety case and maintaining its validity after changes are time-consuming manual work performed by safety experts based on their experience and knowledge. This work is further complicated when supplier components need to be integrated where important details might not be known. By using the concept provided by Digital Dependability Identities (DDI), we present an approach to automatically check evidence validity for safety requirements through leveraging from formal traceability between safety argument and evidence models being both parts of the DDI. This approach reduces the effort for creating and maintaining the system-level safety argument by (a) performing automated evidence analysis for safety requirements, (b) supporting a model-based multi-tier safety engineering process and (c) eliminating the human error source by relying on DDI scripts to encode safety engineering activities. We illustrate our approach using a case study from the railway domain, which focuses on the safety assurance of a train control system (ETCS).