Verifying metamodel coverage of model transformations

Since the object management group (OMG) commenced its model driven architecture (MDA) initiative, there has been considerable activity proposing and building automatic model transformation systems to help implement the MDA concept. Much less attention has been given to the need to ensure that model transformations generate the intended results. This paper explores one aspect of validation and verification for MDA: coverage of the source and/or target metamodels by a set of model transformations. The paper defines the property of metamodel coverage and some corresponding algorithms. This property helps the user assess which parts of a source (or target) metamodel are referenced by a given model transformation set. Some results are presented from a prototype implementation that is built on the eclipse modeling framework (EMF).

Model-Driven safety evaluation with state-event-based component failure annotations

Over the past years, the paradigm of component-based software engineering has been established in the construction of complex mission-critical systems. Due to this trend, there is a practical need for techniques that evaluate critical properties (such as safety, reliability, availability or performance) of these systems. In this paper, we review several high-level techniques for the evaluation of safety properties for component-based systems and we propose a new evaluation model (State Event Fault Trees) that extends safety analysis towards a lower abstraction level. This model possesses a state-event semantics and strong encapsulation, which is especially useful for the evaluation of component-based software systems. Finally, we compare the techniques and give suggestions for their combined usage

Incremental model transformation for the evolution of model-driven systems

Model transformations are an integral part of model-driven development. Incremental updates are a key execution scenario for transformations in model-based systems, and are especially important for the evolution of such systems. This paper presents a strategy for the incremental maintenance of declarative, rule-based transformation executions. The strategy involves recording dependencies of the transformation execution on information from source models and from the transformation definition. Changes to the source models or the transformation itself can then be directly mapped to their effects on transformation execution, allowing changes to target models to be computed efficiently. This particular approach has many benefits. It supports changes to both source models and transformation definitions, it can be applied to incomplete transformation executions, and a priori knowledge of volatility can be used to further increase the efficiency of change propagation.

Model driven distribution of collaborative business processes

In this paper, we present a top down approach for integrated process modelling and distributed process execution. The integrated process model can be utilized for global monitoring and visualization and distributed process models for local execution. Our main focus in this paper is the presentation of the approach to support automatic generation and linking of distributed process models from an integrated process definition.

MQL: A powerful extension to OCL for MOF queries

The Meta-Object Facility (MOF) provides a standardized framework for object-oriented models. An instance of a MOF model contains objects and links whose interfaces are entirely derived from that model. Information contained in these objects can be accessed directly, however, in order to realize the Model-Driven Architecture@trade; (MDA), we must have a mechanism for representing and evaluating structured queries on these instances. The MOF Query Language (MQL) is a language that extends the UML's Object Constraint Language (OCL) to provide more expressive power, such as higher-order queries, parametric polymorphism and argument polymorphism. Not only do these features allow more powerful queries, but they also encourage a greater degree of modularization and re-use, resulting in faster prototyping and facilitating automated integrity analysis. This paper presents an overview of the motivations for developing MQL and also discusses its abstract syntax, presented as a MOF model, and its semantics

Introduction of routine outcome measures: staff reactions and issues for consideration

The aim of this study was to explore clinician reactions to (i) the introduction of routine outcome measures and (ii) the utility of outcomes data in clinical practice. Focus group discussions (n = 34) were conducted with mental health staff (n = 324) at approximately 8 months post implementation of routine outcome measures. A semi-structured interview schedule was used to collect data on two key issues; reactions to the introduction of outcome measures and factors influencing the utility of outcomes data in clinical practice. Data from the discussion groups were analysed using content analysis to isolate emerging themes. While the majority of participants endorsed the collection and utilization of outcomes data, many raised questions about the merits of the initiative. Ambivalence, competing work demands, lack of support from senior medical staff, questionable evidence to support the use of outcome measures, and fear of how outcomes data might be used emerged as key issues. At 8 months post implementation a significant number of clinical staff remained ambivalent about the benefits of outcome measurement and had not engaged in the process. The shift to a service model driven by outcomes and case-mix data will take time and resources to achieve. Implications for nursing staff are discussed.

Towards a standards-based autonomic context management system

Pervasive computing applications must be sufficiently autonomous to adapt their behaviour to changes in computing resources and user requirements. This capability is known as context-awareness. In some cases, context-aware applications must be implemented as autonomic systems which are capable of dynamically discovering and replacing context sources (sensors) at run-time. Unlike other types of application autonomy, this kind of dynamic reconfiguration has not been sufficiently investigated yet by the research community. However, application-level context models are becoming common, in order to ease programming of context-aware applications and support evolution by decoupling applications from context sources. We can leverage these context models to develop general (i.e., application-independent) solutions for dynamic, run-time discovery of context sources (i.e., context management). This paper presents a model and architecture for a reconfigurable context management system that supports interoperability by building on emerging standards for sensor description and classification.