A type-theoretic framework for certified model transformations

"We present a framework based on the Calculus of Inductive Constructions (CIC) and its associated tool the Coq proof assistant to allow certification of model transformations in the context of Model-Driven Engineering (MDE). The approached is based on a semi-automatic translation process from metamodels, models and transformations of the MDE technical space into types, propositions and functions of the CIC technical space. We describe this translation and illustrate its use in a standard case study." [Abstract

Typing in Model Management

International audienceModel management is essential for coping with the complexity introduced by the increasing number and varied nature of artifacts involved in MDE-based projects. Global Model Management (GMM) addresses this issue enabling the representation of artifacts, particularly transformation composition and execution, by a model called a megamodel. Typing information about artifacts can be used for preventing type errors during execution. In this work, we present a type system for GMM that improves its current typing approach and enables formal reasoning about the type of artifacts within a megamodel. This type system is able to capture non-trivial situations such as the use of higher order transformations

Database forensic investigation process models: a review

Database Forensic Investigation (DBFI) involves the identification, collection, preservation, reconstruction, analysis, and reporting of database incidents. However, it is a heterogeneous, complex, and ambiguous field due to the variety and multidimensional nature of database systems. A small number of DBFI process models have been proposed to solve specific database scenarios using different investigation processes, concepts, activities, and tasks as surveyed in this paper. Specifically, we reviewed 40 proposed DBFI process models for RDBMS in the literature to offer up- to-date and comprehensive background knowledge on existing DBFI process model research, their associated challenges, issues for newcomers, and potential solutions for addressing such issues. This paper highlights three common limitations of the DBFI domain, which are: 1) redundant and irrelevant investigation processes; 2) redundant and irrelevant investigation concepts and terminologies; and 3) a lack of unified models to manage, share, and reuse DBFI knowledge. Also, this paper suggests three solutions for the discovered limitations, which are: 1) propose generic DBFI process/model for the DBFI field; 2) develop a semantic metamodeling language to structure, manage, organize, share, and reuse DBFI knowledge; and 3) develop a repository to store and retrieve DBFI field knowledge

A formalisation of deep metamodelling

The final publication is available at Springer via http://dx.doi.org/10.1007/s00165-014-0307-xMetamodelling is one of the pillars of model-driven engineering, used for language engineering and domain modelling. Even though metamodelling is traditionally based on a two-metalevel approach, several researchers have pointed out limitations of this solution and proposed an alternative deep (also called multi-level) approach to obtain simpler system specifications. However, this approach currently lacks a formalisation that can be used to explain fundamental concepts such as deep characterisation, double linguistic/ontological typing and linguistic extension. This paper provides such a formalisation based on the Diagram Predicate Framework, and discusses its practical realisation in the metaDepth tool.This work was partially funded by the SpanishMinistry of Economy and Competitiveness (project “Go Lite” TIN2011- 24139)

Simplified database forensic investigation using metamodeling approach

Database Forensic Investigation (DBFI) domain is a significant field used to identify, collect, preserve, reconstruct, analyze and document database incidents. However, it is a heterogeneous, complex, and ambiguous domain due to the variety and multidimensional nature of database systems. Numerous specific DBFI models and frameworks have been proposed to solve specific database scenarios but there is a lack of structured and unified frameworks to facilitate managing, sharing and reusing of DBFI tasks and activities. Thus, this research developed a DBFI Metamodel (DBFIM) to structure and organize DBFI domain. A Design Science Research Methodology (DSRM) to provide a logical, testable and communicable metamodel was applied in this study. In this methodology, the steps included problem identification, define objectives, design and development, demonstration and evaluation, and communication. The outcome of this study is a DBFIM developed for structuring and organizing DBFI domain knowledge that facilitates the managing, sharing and reusing of DBFI domain knowledge among domain practitioners. DBFIM identifies, recognizes, extracts and matches different DBFI processes, concepts, activities, and tasks from different DBFI models into a developed metamodel, thus, allowing domain practitioners to derive/instantiate solution models easily. The DBFIM was validated using qualitative techniques: comparison against other models; face validity (domain experts); and case study. Comparisons against other models and face validity were applied to ensure completeness, logicalness, and usefulness of DBFIM against other DBFI domain models. Following this, two case studies were selected and implemented to demonstrate the applicability and effectiveness of the DBFIM in the DBFI domain using a DBFIM Prototype (DBFIMP). The results showed that DBFIMP allowed domain practitioners to create their solution models easily based on their requirements

Estado del arte de verificación de transformación de modelos

El Desarrollo de Software Guiado por Modelos (Model-Driven Development, MDD) es un enfoque de ingeniería de software basado en el modelado de un sistema como la principal actividad del desarrollo y la construcción del mismo guiada por transformaciones de dichos modelos. Su éxito depende fuertemente de la disponibilidad de lenguajes y herramientas apropiados para realizar las transformaciones y validar su corrección. En relación a este último punto, este documento presenta un relevamiento del estado del arte de los diferentes enfoques y técnicas de verificación de transformaciones de modelos empleados para MDD. Se analizan las principales características de los enfoques existentes, a saber: basado en casos de prueba, model checking y métodos deductivos. Así mismo se estudian las diferentes técnicas existentes para cada enfoque y se presentan las herramientas utilizadas en la bibliografía, ejemplificando su uso