Systematic Usage of Embedded Modelling Languages in Automated Model Transformation Chains

Annotation of programs using embedded Domain-Specific Languages (embedded DSLs), such as the program annotation facility for the Java programming language, is a well-known practice in computer science. In this paper we argue for and propose a specialized approach for the usage of embedded Domain-Specific Modelling Languages (embedded DSMLs) in Model-Driven Engineering (MDE) processes that in particular supports automated many-step model transformation chains. It can happen that information defined at some point, using an embedded DSML, is not required in the next immediate transformation step, but in a later one. We propose a new approach of model annotation enabling flexible many-step transformation chains. The approach utilizes a combination of embedded DSMLs, trace models and a megamodel. We demonstrate our approach based on an example MDE process and an industrial case study.

Artificial Intelligence Model for Flowable Concrete Mixtures Used in Underwater Construction and Repair

This study explores using artificial neural networks to predict the rheological and mechanical properties of underwater concrete (UWC) mixtures and to evaluate the sensitivity of such properties to variations in mixture ingredients. Artificial neural networks (ANN) mimic the structure and operation of biological neurons and have the unique ability of self-learning, mapping, and functional approximation. Details of the development of the proposed neural network model, its architecture, training, and validation are presented in this study. A database incorporating 175 UWC mixtures from nine different studies was developed to train and test the ANN model. The data are arranged in a patterned format. Each pattern contains an input vector that includes quantity values of the mixture variables influencing the behavior of UWC mixtures (that is, cement, silica fume, fly ash, slag, water, coarse and fine aggregates, and chemical admixtures) and a corresponding output vector that includes the rheological or mechanical property to be modeled. Results show that the ANN model thus developed is not only capable of accurately predicting the slump, slump-flow, washout resistance, and compressive strength of underwater concrete mixtures used in the training process, but it can also effectively predict the aforementioned properties for new mixtures designed within the practical range of the input parameters used in the training process with an absolute error of 4.6, 10.6, 10.6, and 4.4%, respectively.

A Data Model for Content Modelling of Temporal Media

This paper describes a data model for content representation of temporal media in an IP based sensor network. The model is formed by introducing the idea of semantic-role from linguistics into the underlying concepts of formal event representation with the aim of developing a common event model. The architecture of a prototype system for a multi camera surveillance system, based on the proposed model is described. The important aspects of the proposed model are its expressiveness, its ability to model content of temporal media, and its suitability for use with a natural language interface. It also provides a platform for temporal information fusion, as well as organizing sensor annotations by help of ontologies.

Automatização de testes à framework myMIS

Atualmente, verifica-se um aumento na necessidade de software feito à medida do cliente, que se consiga adaptar de forma rápida as constantes mudanças da sua área de negócio. Cada cliente tem os seus problemas concretos que precisa de resolver, não lhe sendo muitas vezes possível dispensar uma elevada quantidade de recursos para atingir os fins pretendidos. De forma a dar resposta a estes problemas surgiram várias arquiteturas e metodologias de desenvolvimento de software, que permitem o desenvolvimento ágil de aplicações altamente configuráveis, que podem ser personalizadas por qualquer utilizador das mesmas. Este dinamismo, trazido para as aplicações sobre a forma de modelos que são personalizados pelos utilizadores e interpretados por uma plataforma genérica, cria maiores desafios no momento de realizar testes, visto existir um número de variáveis consideravelmente maior que numa aplicação com uma arquitetura tradicional. É necessário, em todos os momentos, garantir a integridade de todos os modelos, bem como da plataforma responsável pela sua interpretação, sem ser necessário o desenvolvimento constante de aplicações para suportar os testes sobre os diferentes modelos. Esta tese debruça-se sobre uma aplicação, a plataforma myMIS, que permite a interpretação de modelos orientados à gestão, escritos numa linguagem específica de domínio, sendo realizada a avaliação do estado atual e definida uma proposta de práticas de testes a aplicar no desenvolvimento da mesma. A proposta resultante desta tese permitiu verificar que, apesar das dificuldades inerentes à arquitetura da aplicação, o desenvolvimento de testes de uma forma genérica é possível, podendo as mesmas lógicas ser utilizadas para o teste de diversos modelos distintos.

The Joint UK Land Environment Simulator (JULES), model description – part 1: energy and water fluxes

This manuscript describes the energy and water components of a new community land surface model called the Joint UK Land Environment Simulator (JULES). This is developed from the Met Office Surface Exchange Scheme (MOSES). It can be used as a stand alone land surface model driven by observed forcing data, or coupled to an atmospheric global circulation model. The JULES model has been coupled to the Met Office Unified Model (UM) and as such provides a unique opportunity for the research community to contribute their research to improve both world-leading operational weather forecasting and climate change prediction systems. In addition JULES, and its forerunner MOSES, have been the basis for a number of very high-profile papers concerning the land-surface and climate over the last decade. JULES has a modular structure aligned to physical processes, providing the basis for a flexible modelling platform.

Prototype Generation from Ontology Charts

Semantic Analysis is a business analysis method designed to capture system requirements. While these requirements may be represented as text, the method also advocates the use of Ontology Charts to formally denote the system's required roles, relationships and forms of communication. Following model driven engineering techniques, Ontology Charts can be transformed to temporal Database schemas, class diagrams and component diagrams, which can then be used to produce software systems. A nice property of these transformations is that resulting system design models lend themselves to complicated extensions that do not require changes to the design models. For example, resulting databases can be extended with new types of data without the need to modify the database schema of the legacy system. Semantic Analysis is not widely used in software engineering, so there is a lack of experts in the field and no design patterns are available. This make it difficult for the analysts to pass organizational knowledge to the engineers. This study describes an implementation that is readily usable by engineers, which includes an automated technique that can produce a prototype from an Ontology Chart. The use of such tools should enable developers to make use of Semantic Analysis with minimal expertise of ontologies and MDA.

Extracting Causal Graphs from an Open Provenance Data Model

The open provenance architecture (OPA) approach to the challenge was distinct in several regards. In particular, it is based on an open, well-defined data model and architecture, allowing different components of the challenge workflow to independently record documentation, and for the workflow to be executed in any environment. Another noticeable feature is that we distinguish between the data recorded about what has occurred, emphprocess documentation, and the emphprovenance of a data item, which is all that caused the data item to be as it is and is obtained as the result of a query over process documentation. This distinction allows us to tailor the system to separately best address the requirements of recording and querying documentation. Other notable features include the explicit recording of causal relationships between both events and data items, an interaction-based world model, intensional definition of data items in queries rather than relying on explicit naming mechanisms, and emphstyling of documentation to support non-functional application requirements such as reducing storage costs or ensuring privacy of data. In this paper we describe how each of these features aid us in answering the challenge provenance queries.

Meta, tracer - MOF with traceability

The following document proposes a traceability solution for model-driven development. There as been already previous work done in this area, but so far there has not been yet any standardized way for exchanging traceability information, thus the goal of this project developed and documented here is not to automatize the traceability process but to provide an approach to achieve traceability that follows OMG standards, making traceability information exchangeable between tools that follow the same standards. As such, we propose a traceability meta-model as an extension of MetaObject Facility (MOF)1. Using MetaSketch2 modeling language workbench, we present a modeling language for traceability information. This traceability information then can be used for tool cooperation. Using Meta.Tracer (our tool developed for this thesis), we enable the users to establish traceability relationships between different traceability elements and offer a visualization for the traceability information. We then demonstrate the benefits of using a traceability tool on a software development life cycle using a case study. We finalize by commenting on the work developed.

Uma estratégia dirigida a modelos e baseada em linguagem de descrição arquitetural para linhas de produtos de software

Model-oriented strategies have been used to facilitate products customization in the software products lines (SPL) context and to generate the source code of these derived products through variability management. Most of these strategies use an UML (Unified Modeling Language)-based model specification. Despite its wide application, the UML-based model specification has some limitations such as the fact that it is essentially graphic, presents deficiencies regarding the precise description of the system architecture semantic representation, and generates a large model, thus hampering the visualization and comprehension of the system elements. In contrast, architecture description languages (ADLs) provide graphic and textual support for the structural representation of architectural elements, their constraints and interactions. This thesis introduces ArchSPL-MDD, a model-driven strategy in which models are specified and configured by using the LightPL-ACME ADL. Such strategy is associated to a generic process with systematic activities that enable to automatically generate customized source code from the product model. ArchSPLMDD strategy integrates aspect-oriented software development (AOSD), modeldriven development (MDD) and SPL, thus enabling the explicit modeling as well as the modularization of variabilities and crosscutting concerns. The process is instantiated by the ArchSPL-MDD tool, which supports the specification of domain models (the focus of the development) in LightPL-ACME. The ArchSPL-MDD uses the Ginga Digital TV middleware as case study. In order to evaluate the efficiency, applicability, expressiveness, and complexity of the ArchSPL-MDD strategy, a controlled experiment was carried out in order to evaluate and compare the ArchSPL-MDD tool with the GingaForAll tool, which instantiates the process that is part of the GingaForAll UML-based strategy. Both tools were used for configuring the products of Ginga SPL and generating the product source code

MARISA-MDD: uma abordagem para transformações entre modelos orientados a aspectos: dos requisitos ao projeto detalhado

Aspect Oriented approaches associated to different activities of the software development process are, in general, independent and their models and artifacts are not aligned and inserted in a coherent process. In the model driven development, the various models and the correspondence between them are rigorously specified. With the integration of aspect oriented software development (DSOA) and model driven development (MDD) it is possible to automatically propagate models from one activity to another, avoiding the loss of information and important decisions established in each activity. This work presents MARISA-MDD, a strategy based on models that integrate aspect-oriented requirements, architecture and detailed design, using the languages AOV-graph, AspectualACME and aSideML, respectively. MARISA-MDD defines, for each activity, representative models (and corresponding metamodels) and a number of transformations between the models of each language. These transformations have been specified and implemented in ATL (Atlas Definition Language), in the Eclipse environment. MARISA-MDD allows the automatic propagation between AOV-graph, AspectualACME, and aSideML models. To validate the proposed approach two case studies, the Health Watcher and the Mobile Media have been used in the MARISA-MDD environment for the automatic generation of AspectualACME and aSideML models, from the AOV-graph model

CrossMDA-SPL: uma abordagem para gerência de variabilidades dirigida por modelos e aspectos

This paper proposes a systematic approach to management of variability modelsdriven and aspects using the mechanisms of approaches Aspect-Oriented Software Development (AOSD) and Model-Driven Development (MDD). The main goal of the approach, named CrossMDA-SPL, is to improve the management(gerência), modularization and isolation ou separation of the variability of the LPSs of architecture in a high level of abstraction (model) at the design and implementing phases of development Software Product Lines (SPLs), exploiting the synergy between AOSD and MDD. The CrossMDA-SPL approach defines some artifacts basis for advance the separation clear in between the mandatory (bounden) and optional features in the architecture of SPL. The artifacts are represented by two models named: (i) core model (base domain) - responsible for specify the common features the all members of the SPL, and (ii) variability model - responsible for represent the variables features of SPL. In addition, the CrossMDA-SPL approach is composed of: (i) guidelines for modeling and representation of variability, (ii) CrossMDA-SPL services and process, and (iii) models of the architecture of SPL or product instance of SPL. The guidelines use the advantages of AOSD and MDD to promote a better modularization of the variable features of the architecture of SPL during the creation of core and variability models of the approach. The services and sub-processes are responsible for combination automatically, through of process of transformation between the core and variability models, and the generation of new models that represent the implementation of the architecture of SPL or a instance model of SPL. Mechanisms for effective modularization of variability for architectures of SPL at model level. The concepts are described and measured with the execution of a case study of an SPL for management systems of transport electronic tickets

GingaForAll: linha de Produtos do Middleware Ginga

Many challenges have been imposed on the middleware to support applications for digital TV because of the heterogeneity and resource constraints of execution platforms. In this scenario, the middleware must be highly configurable so that it can be customized to meet the requirements of applications and underlying platforms. This work aims to present the GingaForAll, a software product line developed for the Ginga - the middleware of the Brazilian Digital TV (SBTVD). GingaForAll adds the concepts of software product line, aspect orientation and model-driven development to allow: (i) the specification of the common characteristics and variables of the middleware, (ii) the modularization of crosscutting concerns - both mandatory and concepts variables - through aspects, (iii) the expression of concepts as a set of models that increase the level of abstraction and enables management of various software artifacts in terms of configurable models. This work presents the architecture of the software product line that implements such a tool and architecture that supports automatic customization of middleware. The work also presents a tool that implements the process of generating products GingaForAll

Dos requisitos à arquitetura em linhas de produtos de software: uma estratégia de transformações entre modelos

The tracking between models of the requirements and architecture activities is a strategy that aims to prevent loss of information, reducing the gap between these two initial activities of the software life cycle. In the context of Software Product Lines (SPL), it is important to have this support, which allows the correspondence between this two activities, with management of variability. In order to address this issue, this paper presents a process of bidirectional mapping, defining transformation rules between elements of a goaloriented requirements model (described in PL-AOVgraph) and elements of an architectural description (defined in PL-AspectualACME). These mapping rules are evaluated using a case study: the GingaForAll LPS. To automate this transformation, we developed the MaRiPLA tool (Mapping Requirements to Product Line Architecture), through MDD techniques (Modeldriven Development), including Atlas Transformation Language (ATL) with specification of Ecore metamodels jointly with Xtext , a DSL definition framework, and Acceleo, a code generation tool, in Eclipse environment. Finally, the generated models are evaluated based on quality attributes such as variability, derivability, reusability, correctness, traceability, completeness, evolvability and maintainability, extracted from the CAFÉ Quality Model

MOOGLE: a metamodel-based model search engine

Models are becoming increasingly important in the software development process. As a consequence, the number of models being used is increasing, and so is the need for efficient mechanisms to search them. Various existing search engines could be used for this purpose, but they lack features to properly search models, mainly because they are strongly focused on text-based search. This paper presents Moogle, a model search engine that uses metamodeling information to create richer search indexes and to allow more complex queries to be performed. The paper also presents the results of an evaluation of Moogle, which showed that the metamodel information improves the accuracy of the search.