A Methodology for Automating Assurance Case Generation

TL;DR

This paper presents a structured, automated methodology for generating safety assurance cases in cyber-physical systems, reducing manual effort and increasing reliability in safety certification processes.

Contribution

It introduces a novel automated assurance case generation tool that leverages design artifacts, evidence, and expertise, demonstrated through a remote-control car case study.

Findings

Automated tool effectively constructs safety cases from design artifacts.

Reduces time and effort compared to manual assurance case generation.

Applicable to diverse CPS domains like automotive and medical devices.

Abstract

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.