Using formal metamodels to check consistency of functional views in information systems specification

UML notations require adaptation for applications such as Information Systems (IS). Thus we have defined IS-UML. The purpose of this article is twofold. First, we propose an extension to this language to deal with functional aspects of IS. We use two views to specify IS transactions: the first one is defined as a combination of behavioural UML diagrams (collaboration and state diagrams), and the second one is based on the definition of specific classes of an extended class diagram. The final objective of the article is to consider consistency issues between the various diagrams of an IS-UML specification. In common with other UML languages, we use a metamodel to define IS-UML. We use class diagrams to summarize the metamodel structure and a formal language, B, for the full metamodel. This allows us to formally express consistency checks and mapping rules between specific metamodel concepts. (C) 2007 Elsevier B.V. All rights reserved

Juxtaposing Australian and Canadian Writing

The geographical entities of Australia and Canada house multifarious localities, regions and nations. Juxtaposing literary work emerging from them can open up invaluable new angles of critical inquiry at a moment when literary scholars in both countries seek insight into the relationship between national literatures and transnational forces. Upholding the value of comparing Australian and Canadian literatures is an urgent task at present given that interest in this juxtaposition seems to be diminishing

Towards hybrid model persistence

Change-based persistence has the potential to support faster and more accurate model comparison, merging, as well as a range of analytics activities. However, reconstructing the state of a model by replaying its editing history every time the model needs to be queried or modified can get increasingly expensive as the model grows in size. In this work, we integrate change-based and state-based persistence mechanisms in a hybrid model persistence approach that delivers the best of both worlds. In this paper, we present the design of our hybrid model persistence approach and report on its impact on time and memory footprint for model loading, saving, and storage space usage

Aligning OCL with Domain-Specific Languages to Support Instance-Level Model Queries

The Object Constraint Language (OCL) provides a set of powerful facilities for navigating and querying models in the MOF metamodelling architecture. Currently, OCL queries can be expressed only in the context of MOF metamodels and UML models. This adds an additional burden to the development and use of Domain Specific Languages, which can also benefit from an instance-level querying mechanism. In an effort to address this issue, we report on ongoing work on defining a rigorous approach for aligning the OCL querying and navigation facilities with arbitrary Domain Specific Languages to support instance-level queries. We present a case-study that demonstrates the usefulness and practicality of this approach

Towards efficient comparison of change-based models

Comparison of large models can be time-consuming since every element has to be visited, matched, and compared with its respective element in other models. This can result in bottlenecks in collaborative modelling environments, where identifying differences between two versions of a model is desirable. Reducing the comparison process to only the elements that have been modified since a previous known state (e.g., previous version) could significantly reduce the time required for large model comparison. This paper presents how change-based persistence can be used to localise the comparison of models so that only elements affected by recent changes are compared and to substantially reduce comparison and differencing time (up to 90% in some experiments) compared to state-based model comparison

A multi-arm bandit neighbourhood search for routing and scheduling problems

Abstract Local search based meta-heuristics such as variable neighbourhood search have achieved remarkable success in solving complex combinatorial problems. Local search techniques are becoming increasingly popular and are used in a wide variety of meta-heuristics, such as genetic algorithms. Typically, local search iteratively improves a solution by making a series of small moves. Traditionally these methods do not employ any learning mechanism. We treat the selection of a local search neighbourhood as a dynamic multi- armed bandit (D-MAB) problem where learning techniques for solving the D-MAB can be used to guide the local search process. We present a D-MAB neighbourhood search (D-MABNS) which can be embedded within any meta- heuristic or hyperheuristic framework. Given a set of neighbourhoods, the aim of D-MABNS is to adapt the search sequence, testing promising solutions rst. We demonstrate the eectiveness of D-MABNS on two vehicle routing and scheduling problems, the real-world geographically distributed mainte- nance problem (GDMP) and the periodic vehicle routing problem (PVRP). We present comparisons to benchmark instances and give a detailed analysis of parameters, performance and behaviour. Keywords Meta-heuristic Local search Vehicle routin

Interface Contracts for Workflow+ Models: an Analysis of Uncertainty across Models

Workflow models are used to rigorously specify and reason about diverse types of processes. The Workflow+ (WF+) framework has been developed to support unified modelling of the control and data in processes that can be used to derive assurance cases that support certification. However, WF+ is limited in its support for precise contracts on workflow models, which can enable powerful forms of static analysis and reasoning. In this paper we propose a mechanism for adding interface contracts to WF+ models, which can thereafter be applied to tracing and reasoning about the uncertainty that arises when combining heterogeneous models. We specifically explore this in terms of design models and assurance case models. We argue that some of the key issues in managing some types of uncertainty can be partly addressed by use of interface contract

Using argument notation to engineer biological simulations with increased confidence

The application of computational and mathematical modelling to explore the mechanics of biological systems is becoming prevalent. To significantly impact biological research, notably in developing novel therapeutics, it is critical that the model adequately represents the captured system. Confidence in adopting in silico approaches can be improved by applying a structured argumentation approach, alongside model development and results analysis. We propose an approach based on argumentation from safety-critical systems engineering, where a system is subjected to a stringent analysis of compliance against identified criteria. We show its use in examining the biological information upon which a model is based, identifying model strengths, highlighting areas requiring additional biological experimentation and providing documentation to support model publication. We demonstrate our use of structured argumentation in the development of a model of lymphoid tissue formation, specifically Peyer's Patches. The argumentation structure is captured using Artoo (www.york.ac.uk/ycil/software/artoo), our Web-based tool for constructing fitness-for-purpose arguments, using a notation based on the safety-critical goal structuring notation. We show how argumentation helps in making the design and structured analysis of a model transparent, capturing the reasoning behind the inclusion or exclusion of each biological feature and recording assumptions, as well as pointing to evidence supporting model-derived conclusions

The role of ‘living laboratories’ in accelerating the energy system decarbonization

To decarbonize the energy system by the year 2050, it is crucial that innovations are trialled in a ‘real world’ setting for the purpose of increasing public adoption and support, and for providing insights to decision-makers to ensure their decisions are effective and influential. Together, renewable energy systems, distributed and digitized ‘smart’ energy networks (SEN) provide opportunities to maximize energy efficiency, reduce transmission losses and drive down greenhouse gas emissions. Yet, such integrated Smart Local Energy Systems (SLES) are in the early stages of development and the technologies that underpin them lack testbeds where they can be developed and tested in a real-world environment. Here we demonstrate the potential role of one of Europe’s largest ‘at scale’ multi-vector Smart Energy Network Demonstrator—SEND, developed within a ‘living laboratory’ setting that provides the ‘blueprint’ for the development and testing of low-carbon energy technologies on the UK’s journey to net zero. Based on the SEND platform and data, we have developed and demonstrated several novel AI based smart algorithms for intelligent SLES control and management. We are also working with industry partners to develop a digital twin of the smart energy system on our campus