A Framework for Evaluating Model-Driven Self-adaptive Software Systems

In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven development in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analysing and evaluating the features of model-driven approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the propped model-driven approaches in the related works, and emphasise on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modelling languages and modelling tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition, self-adaptive application, context oriented software developmen

Pattern Reification as the Basis for Description-Driven Systems

One of the main factors driving object-oriented software development for information systems is the requirement for systems to be tolerant to change. To address this issue in designing systems, this paper proposes a pattern-based, object-oriented, description-driven system (DDS) architecture as an extension to the standard UML four-layer meta-model. A DDS architecture is proposed in which aspects of both static and dynamic systems behavior can be captured via descriptive models and meta-models. The proposed architecture embodies four main elements - firstly, the adoption of a multi-layered meta-modeling architecture and reflective meta-level architecture, secondly the identification of four data modeling relationships that can be made explicit such that they can be modified dynamically, thirdly the identification of five design patterns which have emerged from practice and have proved essential in providing reusable building blocks for data management, and fourthly the encoding of the structural properties of the five design patterns by means of one fundamental pattern, the Graph pattern. A practical example of this philosophy, the CRISTAL project, is used to demonstrate the use of description-driven data objects to handle system evolution.Comment: 20 pages, 10 figure

Models in the Cloud: Exploring Next Generation Environmental Software Systems

There is growing interest in the application of the latest trends in computing and data science methods to improve environmental science. However we found the penetration of best practice from computing domains such as software engineering and cloud computing into supporting every day environmental science to be poor. We take from this work a real need to re-evaluate the complexity of software tools and bring these to the right level of abstraction for environmental scientists to be able to leverage the latest developments in computing. In the Models in the Cloud project, we look at the role of model driven engineering, software frameworks and cloud computing in achieving this abstraction. As a case study we deployed a complex weather model to the cloud and developed a collaborative notebook interface for orchestrating the deployment and analysis of results. We navigate relatively poor support for complex high performance computing in the cloud to develop abstractions from complexity in cloud deployment and model configuration. We found great potential in cloud computing to transform science by enabling models to leverage elastic, flexible computing infrastructure and support new ways to deliver collaborative and open science

Attribute based component design: Supporting model driven development in CbSE

In analysing the evolution of Software Engineering, the scale of the components has increased, the requirements for different domains become complex and a variety of different component frameworks and their associated models have emerged. Many modern component frameworks provide enterprise level facilities and services, such as instance management, and component container support, that allow developers to apply if needed to manage scale and complexity. Although the services provided by these frameworks are common, they have different models and implementation. Accordingly, the main problem is, when developing a component based application using a component framework, the design of the components becomes tightly integrated with the framework implementation and the framework model is embedded in the component functionality, and hence reduces reusability. Another problem arose is, the designers must have in-depth knowledge of the implementation of a component framework to be able to model, design and implement the components and take advantages of the services provided. To address these problems, this research proposes the Attribute based Component Design (AbCD) approach which allows developers to model software using logical and abstract components at the specification level. The components encapsulate the provided functionality, as well as the required services, runtime requirements and interaction models using a set of attributes. These attributes are systemically derived by grouping common features and services from light weight component frameworks and heavy weight component frameworks that are available in the literature. The AbCD approach consists of the AbCD Meta-model, which is an extension of the บML meta-model, and the Component Design Guidelines (CDG) that includes core Component based Software Engineering principles to assist the modelling process for designers. To support the AbCD approach, an implementation has been developed as a set of plug-ins, called the AbCD tool suite, for Eclipse IDE. An evaluation of the AbCD approach is conducted by using the tool suite with two case studies. The first case study focuses on abstraction achieved by the AbCD approach and the second focuses on reusability of the components. The evaluation shows that the artefacts produced using the approach provide an alternative architectural view to the design and help to re-factor the design based on aspects. At the same time the evaluation process identified possible improvements in the AbCD meta-model and the tool suite constructed. This research provides a non-invasive approach for designing component based software using model driven development

Learning from AI : new trends in database technology

Recently some researchers in the areas of database data modelling and knowledge representations in artificial intelligence have recognized that they share many common goals. In this survey paper we show the relationship between database and artificial intelligence research. We show that there has been a tendency for data models to incorporate more modelling techniques developed for knowledge representations in artificial intelligence as the desire to incorporate more application oriented semantics, user friendliness, and flexibility has increased. Increasing the semantics of the representation is the key to capturing the "reality" of the database environment, increasing user friendliness, and facilitating the support of multiple, possibly conflicting, user views of the information contained in a database