Assessment of the quality of the text of safety standards with industrial semantic technologies

Abstract

Most safety-critical systems are subject to rigorous assurance processes to justify that the systems are dependable. These processes are typically conducted in compliance with safety standards, e.g., DO-178C for software in aerospace. This can be a prerequisite so that a system is allowed to operate. However, following these standards can be challenging in practice because of issues in their text such as imprecision, ambiguity, and inconsistency. These issues can hinder compliance, delaying it and making it more expensive, or even preventing it. As a solution, we aim to define means that aid in the identification of the issues and thus facilitate their resolution. We have developed an approach for assessment of the quality of the text of safety standards with RQA - Quality Studio, an industrial tool for requirements quality analysis with semantic technologies. The approach is based on the extraction of analysis units from a standard, on the specification and exploitation of ontologies, and on the reuse of metrics provided by RQA - Quality Studio to evaluate text quality. The approach has been applied on the DO-178C standard, assessing its text as a whole and its different main individual parts. The quality of most of the text of the standard can be regarded as high. The most frequent issues in DO-178C are the use of passive voice, of synonyms, and of imprecise modal verbs. To the best of our knowledge, this is the first study that provides a means for a broad and detailed assessment of the quality of the text of safety standards, leading to the identification of specific aspects that could be improved in the text and indicating the extent to which quality issues affect it.