REM4j - A framework for measuring the reverse engineering capability of UML CASE tools

Reverse Engineering is becoming increasingly important in the software development world today as many organizations are battling to understand and maintain old legacy systems. Today’s software engineers have inherited these legacy systems which they may know little about yet have to maintain, extend and improve. Currently there is no framework or strategy that an organisation can use to determine which UML CASE tool to use. This paper sets down such a framework, to allow organisations to base their tool choice on this reliable framework. We present the REM4j tool, an automated tool, for benchmarking UML CASE tools, we then use REM4j to carry out one such evaluation with eleven UML CASE tools. This framework allows us to reach a conclusion as to which is the most accurate and reliable UML CASE tool

A Model Driven Approach to Model Transformations

The OMG's Model Driven Architecture (MDA) initiative has been the focus of much attention in both academia and industry, due to its promise of more rapid and consistent software development through the increased use of models. In order for MDA to reach its full potential, the ability to manipulate and transform models { most obviously from the Platform Independent Model (PIM) to the Platform Specific Models (PSM) { is vital. Recognizing this need, the OMG issued a Request For Proposals (RFP) largely concerned with finding a suitable mechanism for trans- forming models. This paper outlines the relevant background material, summarizes the approach taken by the QVT-Partners (to whom the authors belong), presents a non-trivial example using the QVT-Partners approach, and finally sketches out what the future holds for model transformations

Automating the transformation-based analysis of visual languages

The final publication is available at Springer via http://dx.doi.org/10.1007/s00165-009-0114-yWe present a novel approach for the automatic generation of model-to-model transformations given a description of the operational semantics of the source language in the form of graph transformation rules. The approach is geared to the generation of transformations from Domain-Specific Visual Languages (DSVLs) into semantic domains with an explicit notion of transition, like for example Petri nets. The generated transformation is expressed in the form of operational triple graph grammar rules that transform the static information (initial model) and the dynamics (source rules and their execution control structure). We illustrate these techniques with a DSVL in the domain of production systems, for which we generate a transformation into Petri nets. We also tackle the description of timing aspects in graph transformation rules, and its analysis through their automatic translation into Time Petri netsWork sponsored by the Spanish Ministry of Science and Innovation, project METEORIC (TIN2008-02081/TIN) and by the Canadian Natural Sciences and Engineering Research Council (NSERC)

Engineering bidirectional transformations

Bidirectional transformations, like software, need to be carefully engineered in order to provide guarantees about their correctness, completeness, acceptability and usability. This paper summarises a collection of lectures pertaining to engineering bidirectional transformations using Model-Driven Engineering techniques and technologies. It focuses on stages of a typical engineering lifecycle, starting with requirements and progressing to implementation and verification. It summarises Model-Driven Engineering approaches to capturing requirements, architectures and designs for bidirectional transformations, and suggests an approach for verification as well. It concludes by describing some challenges for future research into engineering bidirectional transformations

Research on conceptual modeling: Themes, topics, and introduction to the special issue

Conceptual modeling continues to evolve as researchers and practitioners reflect on the challenges of modeling and implementing data-intensive problems that appear in business and in science. These challenges of data modeling and representation are well-recognized in contemporary applications of big data, ontologies, and semantics, along with traditional efforts associated with methodologies, tools, and theory development. This introduction contains a review of some current research in conceptual modeling and identifies emerging themes. It also introduces the articles that comprise this special issue of papers from the 32nd International Conference on Conceptual Modeling (ER 2013).This article was supported, in part, by the J. Mack Robinson College of Business at the Georgia State University, the Marriott School of Management at Brigham Young University (EB-201313), and by the GEODAS-BI (TIN2012-37493-C03-03) project from the Spanish Ministry of Education and Competitivity