Less Manual Work for Safety Engineers: Towards an Automated Safety Reasoning with Safety Patterns

TL;DR

This paper introduces an automated safety reasoning approach using logic programming for safety-critical systems, aiding engineers in selecting appropriate safety patterns to control hazards more efficiently.

Contribution

It presents a domain-specific language and logic programming framework for automated safety reasoning, improving decision support for deploying safety patterns in embedded systems.

Findings

Automated identification of controllable hazards.

Automated recommendations for safety pattern deployment.

Application to automotive safety systems.

Abstract

The development of safety-critical systems requires the control of hazards that can potentially cause harm. To this end, safety engineers rely during the development phase on architectural solutions, called safety patterns, such as safety monitors, voters, and watchdogs. The goal of these patterns is to control (identified) faults that can trigger hazards. Safety patterns can control such faults by e.g., increasing the redundancy of the system. Currently, the reasoning of which pattern to use at which part of the target system to control which hazard is documented mostly in textual form or by means of models, such as GSN-models, with limited support for automation. This paper proposes the use of logic programming engines for the automated reasoning about system safety. We propose a domain-specific language for embedded system safety and specify as disjunctive logic programs reasoning principles used by safety engineers to deploy safety patterns, e.g., when to use safety monitors, or watchdogs. Our machinery enables two types of automated safety reasoning: (1) identification of which hazards can be controlled and which ones cannot be controlled by the existing safety patterns; and (2) automated recommendation of which patterns could be used at which place of the system to control potential hazards. Finally, we apply our machinery to two examples taken from the automotive domain: an adaptive cruise control system and a battery management system.