Anitha Murugesan, Isaac Wong, Joaquin Arias, Robert Stroud, Srivatsan Varadarajan, Elmer Salazar, Gopal Gupta, Robin Bloomfield, and John Rushby

Appears in special issue of Theory and Practice of Logic Programming (TPLP), Volume 24, Issue 4, July 2024, pp. 805 - 824

DOI: 10.1017/S1471068424000425

Abstract

In prior work, we introduced the Assurance 2.0 framework that prioritizes the reasoning process, evidence utilization, and explicit delineation of counter-claims (defeaters) and counter-evidence. In this paper, we present our approach to enhancing Assurance 2.0 with semantic rule-based analysis capabilities using common-sense reasoning and answer set programming solvers, specifically s(CASP). By employing these analysis techniques, we examine the unique semantic aspects of assurance cases, such as logical consistency, adequacy, indefeasibility, etc. The application of these analyses provides both system developers and evaluators with increased confidence about the assurance case.

Information about Assurance 2.0 and Clarissa

Paper

BibTeX Entry

\newcommand{\arxiv}[1]{\href{https://arxiv.org/abs/#1}{\tt arXiv:#1}}

@ARTICLE{Murugesan-all24:TDLP,
   AUTHOR = {Anitha Murugesan and Isaac Wong and Joaqu\'{\i}n Arias
     and Robert Stroud and Srivatsan Varadarajan and Elmer Salazar
     and Gopal Gupta and Robin Bloomfield and John Rushby},
   TITLE = {Automating Semantic Analysis of System Assurance Cases
     using Goal-directed ASP},
   JOURNAL = {Theory and Practice of Logic Programming},
   YEAR = 2024,
   VOLUME = 24,
   NUMBER = 4,
   MONTH   = jul,
   PAGES = {805--824},
   DOI = {10.1017/S1471068424000425},
   NOTE = {Also available as \arxiv{2408.11699}}
}