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This paper presents an approach to P system verification using the Spin model checker. It proposes a P system implementation in PROMELA, the modeling language accepted by SPIN. It also provides the theoretical background for transforming the temporal logic properties expressed for the P system into properties of the executable implementation. Furthermore, a comparison between P systems verification using SPIN and NUSMV is realized. The results obtained show that the PROMELA implementation is more adequate, especially for verifying more complex models, such as P systems that model ecosystems. [ABSTRACT FROM AUTHOR]

A language L is called the orthogonal shuffle of the language L1 with the language L2, along the trajectory set T if every word in L is uniquely obtained as the shuffle between a word in L1, a word in L2 along a trajectory word in T. In this paper we investigate properties of the orthogonal shuffle on trajectories, as well as several types of language equations using this language operation. As a corollary, we obtain several properties of orthogonal catenation, orthogonal literal shuffle and orthogonal insertion. [ABSTRACT FROM AUTHOR]

The process of engineering software-intensive systems that comply with their Certification and Accreditation (C&A) requirements involves many critical decision-making activities for the related stakeholders. Considering the exhaustive nature of C&A activities together with the complexity of software-intensive systems, effective decision making relies heavily on the ways to understand and structure the problem domain concepts concerning decision points for interpretation, applicability, scope, evaluation, and impact of the enforced C&A requirements. These decision points are further complicated by natural language specifications of inherently non-functional C&A requirements scattered across multiple regulatory documents with complex interdependencies at different levels of abstractions in the organizational hierarchy, which often result in subjective interpretations and non-standard implementations of the C&A process. To address these issues, we define a systematic methodology using novel techniques from software Requirements Engineering (RE) and knowledge engineering for understanding and structuring the problem domain concepts based on a uniform representation format that promotes common understanding among stakeholders. Specifically, we use advanced ontological engineering techniques driven by theoretical RE foundations to systematically elicit, model, understand, and analyze problem domain concepts concerning significant and difficult decision points throughout the C&A process. We demonstrate the appropriateness of our methodology in creating decision support problem domain ontology using several examples derived from our experiences on automating the Department of Defense Information Technology Security C&A Process (DITSCAP). [ABSTRACT FROM AUTHOR]