Certus: A domain specific language for confidence assessment in assurance cases

TL;DR

Certus is a domain-specific language designed to improve confidence assessment in assurance cases by enabling users to express their judgments with fuzzy sets and transparent propagation syntax, demonstrated through an automotive example.

Contribution

Introduces Certus, a novel language for quantitative confidence assessment using fuzzy sets and clear syntax, addressing limitations of existing methods.

Findings

Certus effectively models confidence with fuzzy sets.

The language's syntax allows transparent confidence propagation.

Applied successfully to an automotive assurance case.

Abstract

Assurance cases (ACs) are prepared to argue that a system has satisfied critical quality attributes. Many methods exist to assess confidence in ACs, including quantitative methods that represent confidence numerically. While quantitative methods are attractive in principle, existing methods suffer from issues related to interpretation, subjectivity, scalability, dialectic reasoning, and trustworthiness, which have limited their adoption. This paper introduces Certus, a domain specific language for quantitative confidence assessment. In Certus, users describe their confidence with fuzzy sets, which allow them to represent their judgment using vague, but linguistically meaningful terminology. Certus includes syntax to specify confidence propagation using expressions that can be easily inspected by users. To demonstrate the concept of the language, Certus is applied to a worked example from the automotive domain.