Treasure: Improved Automated Traceability for Assurance of Safety-Critical Systems

Summary

Funded by: Junta de Comunidades de Castilla-La Mancha
From: 01/01/2020 until: 20/03/2023
Main Researchers: de la Vara González, José Luis

Abstract

Safety-critical systems (SCS) are those whose failure can harm people, property, or the environment, e.g. the systems used in aeronautics. Society increasingly relies on these systems for transport, healthcare, energy, or communications, and their dependability must be guaranteed. Traceability is one of the most valuable assets for SCS assurance and is required for system certification.
Traceability information shows how a system has evolved during its lifecycle and how its dependability has been addressed. Deficient traceability of SCS has led to many issues in the past, including accidents. In practice, traceability management is a challenging, labour-intensive, and expensive activity. Researchers have been struggling for the last two decades to develop means that can improve it, and automated proposals are arguably positioned as the most promising ones for enhancing traceability management. However, there exist a gap between academia and industry that, on the one hand, hinders a wide adoption of advanced research results and, on the other hand, results in a lack of alignment between research results and current practices. This ultimately leads to improvable automated traceability.
Treasure aims to increase the cost-effectiveness of automated traceability for SCS assurance by developing a model-driven and ontology-based approach. Model-driven traceability approaches have been largely researched but their transfer to practice is limited, whereas ontology-based ones are used in industry but do not sufficiently exploit research results. Both types of approaches enable automated traceability and their combination can further improve it.
Treasure will specify a framework for assessing trace quality throughout the entire SCS traceability process, develop a model-driven and ontology-based approach for automating traceability management, and demonstrate that the approach is more efficient than prior automated traceability approaches. This will lead to a higher confidence in SCS’ dependability, as the assurance aspects related to traceability will be better addressed.