Trace queries for safety requirements in high assurance systems

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Abstract

[Context and motivation] Safety critical software systems pervade almost every facet of our lives. We rely on them for safe air and automative travel, healthcare diagnosis and treatment, power generation and distribution, factory robotics, and advanced assistance systems for special-needs consumers. [Question/Problem] Delivering demonstrably safe systems is difficult, so certification and regulatory agencies routinely require full life-cycle traceability to assist in evaluating them. In practice, however, the traceability links provided by software producers are often incomplete, inaccurate, and ineffective for demonstrating software safety. Also, there has been insufficient integration of formal method artifacts into such traceability. [Principal ideas/results] To address these weaknesses we propose a family of reusable traceability queries that serve as a blueprint for traceability in safety critical systems. In particular we present queries that consider formal artifacts, designed to help demonstrate that: 1) identified hazards are addressed in the safety-related requirements, and 2) the safety-related requirements are realized in the implemented system. We model these traceability queries using the Visual Trace Modeling Language, which has been shown to be more intuitive than the defacto SQL standard. [Contribution] Practitioners building safety critical systems can use these trace queries to make their traceability efforts more complete, accurate and effective. This, in turn, can assist in building safer software systems and in demonstrating their adequate handling of hazards. © 2012 Springer-Verlag.

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APA

Cleland-Huang, J., Heimdahl, M., Huffman Hayes, J., Lutz, R., & Maeder, P. (2012). Trace queries for safety requirements in high assurance systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7195 LNCS, pp. 179–193). https://doi.org/10.1007/978-3-642-28714-5_16

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