An Open Platform for Modeling Method Conceptualization: The OMiLAB Digital Ecosystem

This paper motivates, describes, demonstrates in use, and evaluates the Open Models Laboratory (OMiLAB)—an open digital ecosystem designed to help one conceptualize and operationalize conceptual modeling methods. The OMiLAB ecosystem, which a generalized understanding of “model value” motivates, targets research and education stakeholders who fulfill various roles in a modeling method\u27s lifecycle. While we have many reports on novel modeling methods and tools for various domains, we lack knowledge on conceptualizing such methods via a full-fledged dedicated open ecosystem and a methodology that facilitates entry points for novices and an open innovation space for experienced stakeholders. This gap continues due to the lack of an open process and platform for 1) conducting research in the field of modeling method design, 2) developing agile modeling tools and model-driven digital products, and 3) experimenting with and disseminating such methods and related prototypes. OMiLAB incorporates principles, practices, procedures, tools, and services required to address the issues above since it focuses on being the operational deployment for a conceptualization and operationalization process built on several pillars: 1) a granularly defined “modeling method” concept whose building blocks one can customize for the domain of choice, 2) an “agile modeling method engineering” framework that helps one quickly prototype modeling tools, 3) a model-aware “digital product design lab”, and 4) dissemination channels for reaching a global community. In this paper, we demonstrate and evaluate the OMiLAB in research with two selected application cases for domain- and case-specific requirements. Besides these exemplary cases, OMiLAB has proven to effectively satisfy requirements that almost 50 modeling methods raise and, thus, to support researchers in designing novel modeling methods, developing tools, and disseminating outcomes. We also measured OMiLAB’s educational impact

Tackling Traceability Challenges through Modeling Principles in Methodologies Underpinned by Metamodels.

Traceability is recognized to be essential for supporting software development. However, a number of traceability issues are still open, such as link semantics formalization or traceability process models. Traceability methodologies underpinned by metamodels are a promising approach. However current metamodels still have serious limitations. Concerning methodologies in general, three hierarchical layered levels have been identified: metamodel, methodology and project. Metamodels do not often properly support this architecture, and that results in semantic problems at the time of specifying the methodology. Another reason is that they provide extensive predefined sets of types for describing project attributes, while these project attributes are domain specific and, sometimes, even project specific. This paper introduces two complementary modeling principles to overcome these limitations, i.e. the metamodeling three layer hierarchy, and power-type patterns modeling principles. Mechanisms to extend and refine traceability models are inherent to them. The paper shows that, when methodologies are developed from metamodels based on these two principles, the result is a methodology well fitted to project features. Links semantics is also improved

MODEL-BASED PREDICTIVE ANALYTICS FOR ADDITIVE AND SMART MANUFACTURING

Qualification and certification for additive and smart manufacturing systems can be uncertain and very costly. Using available historical data can mitigate some costs of producing and testing sample parts. However, use of such data lacks the flexibility to represent specific new problems which decreases predictive accuracy and efficiency. To address these compelling needs, in this dissertation modeling techniques are introduced that can proactively estimate results expected from additive and smart manufacturing processes swiftly and with practical levels of accuracy and reliability. More specifically, this research addresses the current challenges and limitations posed by use of available data and the high costs of new data by tailoring statistics-based metamodeling techniques to enable affordable prediction of these systems. The result is an integrated approach to customize and build predictive metamodels for the unique features of additive and smart manufacturing systems. This integrated approach is composed of five main parts that cover the broad spectrum of requirements. A domain-driven metamodeling approach uses physics-based knowledge to optimally select the most appropriate metamodeling algorithm without reliance upon statistical data. A maximum predictive error updating method iteratively improves predictability from a given dataset. A grey-box metamodeling approach combines statistics-based black-box and physics-based white-box models to significantly increase predictive accuracy with less expensive data overall. To improve computational efficiency for large datasets, a dynamic metamodeling method modifies the traditional Kriging technique to improve its efficiency and predictability for smart manufacturing systems. Finally, a super-metamodeling method optimizes results regardless of problem conditions by avoiding the challenge with selecting the most appropriate metamodeling algorithm. To realize the benefits of all five approaches, an integrated metamodeling process was developed and implemented into a tool package to systematically select the suitable algorithm, sampling method, and combination of models. All the functions of this tool package were validated and demonstrated by the use of two empirical datasets from additive manufacturing processes

Metamodels of information technology best practices frameworks

This article deals with the generation and application of ontological metamodels of frameworks of best practices in IT. The ontological metamodels represent the logical structures and fundamental semantics of framework models and constitute adequate tools for the analysis, adaptation, comparison and integration of the frameworks of best practices in IT. The MetaFrame methodology for the construction of the metamodels, founded on the discipline of the conceptual metamodelling and on the extended Entity/Relationship methodology is described herein, as well as the metamodels of the best practices for the outsourcing of IT, the eSCM-SP v2.01 (eSourcing Capability Model for Service Providers) and the eSCM-CL v1.1 (eSourcing Capability Model for Client Organizations), constructed according to the MetaFrame methodology

SDK development for bridging heterogeneous data sources through connect bridge platform

Nesta dissertação apresentou-se um SDK para a criação de conectores a integrar com o CB Server, que pretende: acelerar o desenvolvimento, garantir melhores práticas e simplificar as diversas atividades e tarefas no processo de desenvolvimento. O SDK fornece uma API pública e simples, suportada por um conjunto de ferramentas, que facilitam o processo de desenvolvimento, explorando as facilidades disponibilizadas através da API. Para analisar a exatidão, viabilidade, integridade e acessibilidade da solução apresentam-se dois exemplos e casos de estudo. Através dos casos de estudo foi possível identificar uma lista de problemas, de pontos sensíveis e melhorias na solução proposta. Para avaliar a usabilidade da API, uma metodologia baseada em vários métodos de avaliação de usabilidade foi estabelecida. O múltiplo caso de estudo funciona como o principal método de avaliação, combinando vários métodos de pesquisa. O caso de estudo consiste em três fases de avaliação: um workshop, uma avaliação heurística e uma análise subjetiva. O caso de estudo envolveu três engenheiros de software (incluindo programadores e avaliadores). A metodologia aplicada gerou resultados com base num método de inspeção, testes de utilizador e entrevistas. Identificou-se não só pontos sensíveis e falhas no código-fonte, mas também problemas estruturais, de documentação e em tempo de execução, bem como problemas relacionados com a experiência do utilizador. O contexto do estudo é apresentado de modo a tirar conclusões acerca dos resultados obtidos. O trabalho futuro incluirá o desenvolvimento de novas funcionalidades. Adicionalmente, pretende-se resolver problemas encontrados na metodologia aplicada para avaliar a usabilidade da API, nomeadamente problemas e falhas no código fonte (por exemplo, validações) e problemas estruturais.In this dissertation, we present an SDK for the creation of connectors to integrate with CB Server which accelerates deployment, ensures best practices and simplifies the various activities and tasks in the development process. The SDK provides a public and simple API leveraged by a set of tools around the API developed which facilitate the development process by exploiting the API facilities. To analyse the correctness, feasibility, completeness, and accessibility of our solution, we presented two examples and case studies. From the case studies, we derived a list of issues found in our solution and a set of proposals for improvement. To evaluate the usability of the API, a methodology based on several usability evaluation methods has been established. Multiple case study works as the main evaluation method, combining several research methods. The case study consists of three evaluation phases – a hands-on workshop, a heuristic evaluation and subjective analysis. The case study involved three computer science engineers (including novice and expert developers and evaluators). The applied methodology generated insights based on an inspection method, a user test, and interviews. We identify not only problems and flaws in the source code, but also runtime, structural and documentation problems, as well as problems related to user experience. To help us draw conclusion from the results, we point out the context of the study. Future work will include the development of new functionalities. Additionally, we aim to solve problems found in the applied methodology to evaluate the usability of the API, namely problems and flaws in the source code (e.g. validations) and structural problems

ON THE CHALLENGE OF A SEMI-AUTOMATIC TRANSFORMATION PROCESS IN MODEL DRIVEN ENTERPRISE INFORMATION SYSTEMS

Recently, Model Driven Engineering (MDE) approaches have been proposed for supporting the development, maintenance and evolution of software systems. Model driven architecture (MDA) from OMG (Object Management Group), “Software Factories” from Microsoft and the Eclipse Modelling Framework (EMF) from IBM are among the most representative MDE approaches. Nowadays, it is well recognized that model transformations are at the heart of these approaches and represent as a consequence one of the most important operations in MDE. However, despite the multitude of model transformation languages proposals emerging from university and industry, these transformations are often created manually. In this paper we present in the first part our previous works towards automation of the transformation process in the context of MDA. It consists on an extended architecture which introduces mapping and matching as first class entities in the transformation process, represented by models and metamodels. Our architecture is enforced by a methodology which details the different steps leading to a semi-automatic transformation process. In the second part, we propose the illustration of the architecture and methodology to the main case of transforming a PIM into PSM

Multi-level constraints

Meta-modelling and domain-specific modelling languages are supported by multi-level modelling which liberates model-based engineering from the traditional two-level type-instance language architecture. Proponents of this approach claim that multi-level modelling increases the quality of the resulting systems by introducing a second abstraction dimension and thereby allowing both intra-level abstraction via sub-typing and inter-level abstraction via meta-types. Modelling approaches include constraint languages that are used to express model semantics. Traditional languages, such as OCL, support intra-level constraints, but not inter-level constraints. This paper motivates the need for multi-level constraints, shows how to implement such a language in a reflexive language architecture and applies multi-level constraints to an example multi-level model

Approaching the Model-Driven Generation of Feedback to Remove Software Performance Flaws

Abstract—The problem of interpreting results of perfor-mance analysis and providing feedback on software models to overcome performance flaws is probably the most critical open issue in the field of software performance engineering. Automation in this step would help to introduce perfor-mance validation as an integrated activity in the software lifecycle, without dramatically affecting the daily practices of software developers. In this paper we approach the problem with model-driven techniques, on which we build a general solution. Basing on the concept of performance antipatterns, that are bad practices in software modeling leading to performance flaws, we introduce metamodels and transformations that can support the whole process of flaw detection and solution. The approach that we propose is notation-independent and can be embedded in any (existing or future) concrete modeling notation by using weaving models and automatically generated model transformations. Finally, we discuss the issues opened from this work and the future achievements that are at the hand in this domain thanks to model-driven techniques

A Framework to Formalise the MDE Foundations

International audienceDomain-Specific Language (DSL) are getting more and more popular and are being used in critical systems like aerospace and car industries. Methods for simulating and validating DSL models are now necessary in order to make the new software generation more reliable and less costly. Developing analysis tools for DSL requires the definition of models semantics. In this paper, we propose a framework to give a formal foundation of the Model-Driven Engineering (MDE) approach. We separate the usually common notions of models and modelling languages associating to each of them a different goal. In order to prove the consistency of our proposal we express a subset of EMOF, its static semantics and validate its meta-circularity