Guided Safety Analysis for Cyber-Physical Systems
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Solution Overview
Problem
Current tools for maintaining safety cases in software-intensive systems, particularly those interacting with Cyber-Physical Systems, face challenges in efficiently updating trace links and recertifying modified versions, leading to high costs and limited innovation due to the complexity of identifying changes and their safety impacts.
Innovation Solution
The Safety Artifact Forest Analysis (SAFA) method automatically identifies the impact of system-wide changes on previously certified safety assurance cases by generating delta views and providing actionable recommendations to update safety cases, using traceability paths and heuristics to visualize changes and highlight potential safety issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional traceability methods are used to maintain safety cases, then safety assurance is achieved, but the cost and effort of updating safety cases increases significantly
Solution Approach 1:
The system performs preliminary analysis by automatically generating artifact trees and comparing them across versions before full recertification is needed. This preliminary action identifies which safety case elements are actually impacted by changes, allowing organizations to focus resources only on those specific areas rather than performing complete recertification.
Solution Approach 2:
The safety case is segmented into discrete artifact trees that can be independently analyzed and compared. Each artifact tree represents a specific hazard and its mitigation artifacts, allowing selective updating of only those segments that are impacted by changes, rather than treating the entire safety case as a monolithic unit requiring full review.
2Reliability
If comprehensive traceability analysis is performed to identify all safety impacts, then safety is maintained, but the complexity of the process increases
Solution Approach 1:
The system introduces an intermediary automated analysis layer that sits between the source code/artifact changes and the safety case updates. This intermediary automatically generates artifact trees, performs comparisons, and identifies impacted safety elements, transforming a complex manual analysis process into a standardized automated procedure.
Solution Approach 2:
The manual mechanical process of tracing through artifacts and identifying safety impacts is replaced with an automated computational system. The electronic processor automatically generates artifact trees, compares versions, and produces delta views, substituting human manual analysis with algorithmic processing.
3Reliability
If the entire safety case is recertified for every system modification, then safety is ensured, but innovation is limited due to high recertification costs
Solution Approach 1:
Instead of performing complete recertification (excessive action), the system performs partial analysis focused only on the specific artifact trees and safety elements that are actually impacted by changes. This partial action is sufficient to ensure safety for modified portions while avoiding the unnecessary overhead of full recertification.
Solution Approach 2:
The system provides feedback through delta views that clearly show which safety case elements are impacted by changes. This feedback mechanism enables safety analysts to make informed decisions about which areas require attention, creating a responsive system that adapts the recertification scope to the actual changes made.
Data Source
AI summary
Systems and methods for maintaining the safety of a software-based system. One method includes automatically generating a first artifact tree for a hazard for a first version of the system and automatically transforming the first artifact tree into a first augmented tree using a set of heuristics. The method also includes automatically generating a second artifact tree for the hazard for a second version of the system and automatically transforming the second artifact tree for the hazard into a second augmented tree using the set of heuristics. The method further includes automatically comparing the first augmented tree and the second augmented tree to generate a delta view, and automatically generating, based on the delta view, at least one selected from a group consisting of a safety warning for the second version of the software-based system and an actionable recommendation to maintain safety of the second version of the software-based system.


