Relational architecture description language for software families

Software Product-Line Engineering has emerged in recent years, as an important strategy for maximising reuse within the context of a family of related products. In current approaches to software product-lines, there is general agreement that the definition of a reference-architecture for the product-line is an important step in the software engineering process. In this paper we introduce ADLARS, a new form of architecture Description language that places emphasis on the capture of architectural relationships. ADLARS is designed for use within a product-line engineering process. The language supports both the definition of architectural structure, and of important architectural relationships. In particular it supports capture of the relationships between product features, component and task architectures, interfaces and parameter requirements.

Assembling a consistent set of sentences in relational probabilistic logic with stochastic independence

We examine the representation of judgements of stochastic independence in probabilistic logics. We focus on a relational logic where (i) judgements of stochastic independence are encoded by directed acyclic graphs, and (ii) probabilistic assessments are flexible in the sense that they are not required to specify a single probability measure. We discuss issues of knowledge representation and inference that arise from our particular combination of graphs, stochastic independence, logical formulas and probabilistic assessments.

Propositional and Relational Bayesian Networks Associated with Imprecise and Qualitative Probabilistic Assessments

This paper investigates a representation language with flexibility inspired by probabilistic logic and compactness inspired by relational Bayesian networks. The goal is to handle propositional and first-order constructs together with precise, imprecise, indeterminate and qualitative probabilistic assessments. The paper shows how this can be achieved through the theory of credal networks. New exact and approximate inference algorithms based on multilinear programming and iterated/loopy propagation of interval probabilities are presented; their superior performance, compared to existing ones, is shown empirically.

Inequality, state ownership and the European Union: How economic context and economic ideology shape support for the European Union

This article investigates the extent to which economic ideology affects people's support for European Union integration and how this is conditioned by economic context. We argue that people on the economic left who live in a country with conditions of high income inequality and little state ownership will support European integration, because more integration would move public policy in a left-wing direction. By contrast, people on the left who live in a country with conditions of low income inequality and widespread public ownership are likely to be eurosceptic, as further integration would result in a more right-wing public policy. We empirically confirm our hypotheses and discuss the implications for European Union democracy.

Assessing the Societal Impact of Research: The Relational Engagement Approach

Marketing and policy researchers seeking to increase the societal impact of their scholarship should engage directly with relevant stakeholders. For maximum societal effect, this engagement needs to occur both within the research process and throughout the complex process of knowledge transfer. A relational engagement approach to research impact is proposed as complementary and building upon traditional approaches. Traditional approaches to impact employ bibliometric measures and focus on the creation and use of journal articles by scholarly audiences, an important but incomplete part of the academic process. The authors suggest expanding the strategies and measures of impact to include process assessments for specific stakeholders across the entire course of impact: from the creation, awareness, and use of knowledge to societal impact. This relational engagement approach involves the co-creation of research with audiences beyond academia. The authors hope to begin a dialogue on the strategies researchers can make to increase the potential societal benefits of their research.