CODEGER-UWE - Model Driven Web Application Development Tool

In this paper, we present a CODEGER-UWE tool tool to support model-driven web application development. The CODEGER-UWE tool has integrated rule for transformation Model and code generation rules to create web applications for the JSF platform automatically. CODEGER-UWE implemented as a plugin for the MagicDraw tool which allows the generation of source code from UWE models that correspond to the components of the MVC model. This is a tool with a clear, handy development process, applying tools to develop web applications will greatly reduce the time for developing Web applications. Keywords: CODEGER-UWE, Model driven web applications development, Model driven software development, Web application development tools, automated code generation.

A Process Model for Component-Based Model-Driven Software Development

Developing high quality, reliable and on time software systems is challenging due to the increasing size and complexity of these systems. Traditional software development approaches are not suitable for dealing with such challenges, so several approaches have been introduced to increase the productivity and reusability during the software development process. Two of these approaches are Component-Based Software Engineering (CBSE) and Model-Driven Software Development (MDD) which focus on reusing pre-developed code and using models throughout the development process respectively. There are many research studies that show the benefits of using software components and model-driven approaches. However, in many cases the development process is either ad-hoc or not well-defined. This paper proposes a new software development process model that merges CBSE and MDD principles to facilitate software development. The model is successfully tested by applying it to the development of an e-learning system as an exemplar case study.

Applied Artifact-Based Analysis for Architecture Consistency Checking

The usage of models within model-driven software development aims at facilitating complexity management of the system under development and closing the gap between the problem and the solution domain. Utilizing model-driven software development (MDD) tools for agile development can also increase the complexity within a project. The huge number of different artifacts and relations, their different kinds, and the high degree of automation hinder the understanding, maintenance, and evolution within MDD projects. A systematic approach to understand and manage MDD projects with a focus on its artifacts and corresponding relations is necessary to handle the complexity. The artifact-based analysis presented in this paper is such an approach. This paper gives an overview of different contributions of the artifact-based analysis but focuses on a specific kind of analysis: architecture consistency checking of model-driven development projects. By applying this kind of analyses, differences between the desired architecture and the actual architecture of the project at a specific point in time can be revealed.

Evaluation of a Model-driven Knowledge Storage and Retrieval IDE for Interactive HRI Systems

Efficient storage and querying of long-term human–robot interaction data requires application developers to have an in-depth understanding of the involved domains. Creating syntactically and semantically correct queries in the development process is an error prone task which can immensely impact the interaction experience of humans with robots and artificial agents. To address this issue, we present and evaluate a model-driven software development approach to create a long-term storage system to be used in highly interactive HRI scenarios. We created multiple domain-specific languages that allow us to model the domain and seamlessly embed its concepts into a query language. Along with corresponding model-to-model and model-to-text transformations, we generate a fully integrated workbench facilitating data storage and retrieval. It supports developers in the query design process and allows in-tool query execution without the need to have prior in-depth knowledge of the domain. We evaluated our work in an extensive user study and can show that the generated tool yields multiple advantages compared to the usual query design approach.