Supporting conceptualisation processes in collaborative networks: a case study on an R&D project

The development of new products or processes involves the creation, re-creation and integration of conceptual models from the related scientific and technical domains. Particularly, in the context of collaborative networks of organisations (CNO) (e.g. a multi-partner, international project) such developments can be seriously hindered by conceptual misunderstandings and misalignments, resulting from participants with different backgrounds or organisational cultures, for example. The research described in this article addresses this problem by proposing a method and the tools to support the collaborative development of shared conceptualisations in the context of a collaborative network of organisations. The theoretical model is based on a socio-semantic perspective, while the method is inspired by the conceptual integration theory from the cognitive semantics field. The modelling environment is built upon a semantic wiki platform. The majority of the article is devoted to developing an informal ontology in the context of a European R&D project, studied using action research. The case study results validated the logical structure of the method and showed the utility of the method

Evaluating the quality of a set of modelling languages used in combination: A method and a tool

[EN] Modelling languages have proved to be an effective tool to specify and analyse various perspectives of enterprises and information systems. In addition to modelling language designs, works on model quality and modelling language quality evaluation have contributed to the maturity of the model-driven engineering (MDE) field. Although consolidated knowledge on quality evaluation is still relevant to this scenario, in previous works, we have identified misalignments between the topics that academia is addressing and the needs of industry in applying MDE, thus identifying some remaining challenges. In this paper, we focus on the need for a method to evaluate the quality of a set of modelling languages used in combination within a MDE environment. This paper presents MMQEF (Multiple Modelling language Quality Evaluation Framework), describing its foundations, presenting its method components and discussing its trade-offs. (C) 2018 Elsevier Ltd. All rights reserved.This work was supported by COLCIENCIAS (Colombia) (grant 512, 2010); the European Commision FP7 Project CaaS (611351).Giraldo-Velásquez, FD.; España Cubillo, S.; Giraldo, WJ.; Pastor López, O. (2018). Evaluating the quality of a set of modelling languages used in combination: A method and a tool. Information Systems. 77:48-70. https://doi.org/10.1016/j.is.2018.06.002S48707

Automated modelling assistance by integrating heterogeneous information sources

Model-Driven Engineering (MDE) uses models as its main assets in the software development process. The structure of a model is described through a metamodel. Even though modelling and meta-modelling are recurrent activities in MDE and a vast amount of MDE tools exist nowadays, they are tasks typically performed in an unassisted way. Usually, these tools cannot extract useful knowledge available in heterogeneous information sources like XML, RDF, CSV or other models and meta-models. We propose an approach to provide modelling and meta-modelling assistance. The approach gathers heterogeneous information sources in various technological spaces, and represents them uniformly in a common data model. This enables their uniform querying, by means of an extensible mechanism, which can make use of services, e.g., for synonym search and word sense analysis. The query results can then be easily incorporated into the (meta-)model being built. The approach has been realized in the Extremo tool, developed as an Eclipse plugin. Extremo has been validated in the context of two domains { production systems and process modelling { taking into account a large and complex industrial standard for classi cation and product description. Further validation results indicate that the integration of Extremo in various modelling environments can be achieved with low e ort, and that the tool is able to handle information from most existing technological spacesThis work was supported by the Ministry of Education of 1256 Spain (FPU grant FPU13/02698); the Spanish MINECO (TIN2014-52129-R);1257 the R&D programme of the Madrid Region (S2013/ICE-3006); the Austrian 1258 agency for international mobility and cooperation in education, science and re1259 search (OeAD) by funds from the Austrian Federal Ministry of Science, Research 1260 and Economy - BMWFW (ICM-2016-04969

Use of domain-specific language in test automation

The primary aim of this research project was to investigate techniques to replace the complicated process of testing embedded systems in automotive domain. The multi-component domain was composed of different hardware to be used in testing procedure which increased the level of difficulty in testing for an operator. As a result, an existing semi-automated testing procedure was replaced by more simpler and efficient framework (ViBATA). A key step taken in this scenario was the replacement of manual GUI interface with the scriptable one to enhance the automation. This was achieved by building a Domain-specific language which allowed test definition in the form of human readable scripts which could be stored for later use. A DSL is a scripting language defined for a particular domain with compact expressiveness. In this case the domain is testing embedded systems in general and automotive systems in particular. The final product was a test case specification document in the form of XML as an output of generated code from this DSL which will be input to ViBATA to make test specification component automated. In this research a comparative analysis of existing DSLs for alternative domains and investigation of their applicability to the presented domain was also performed. The technologies used in this project are Xtext to define the DSL grammar, Xtend to generate code in Java and Simple framework to generate output in XML. The stages involved in DSL development and how these stages were implemented is covered in this thesis. The developed DSL for this domain is tested for automotive and calculator systems in this thesis which proved that this is more general and flexible. The DSL is consistent, efficient and automated test specification component of testing framework in embedded systems

Flexible Views for View-based Model-driven Development

Modern software development faces the problem of fragmentation of information across heterogeneous artefacts in different modelling and programming languages. In this dissertation, the Vitruvius approach for view-based engineering is presented. Flexible views offer a compact definition of user-specific views on software systems, and can be defined the novel ModelJoin language. The process is supported by a change metamodel for metamodel evolution and change impact analysis

Systematic literature review of domain-oriented specification techniques

Context: The popularity of domain-specific languages and model driven development has made the tacit use of domain knowledge in system development more tangible. Our vision is a development process where a (software) system specification is based on multiple domain models, and where the specification method is built from cognitive concepts, presumably derived from natural language. Goal: To realize this vision, we evaluate and reflect upon the existing literature in domain-oriented specification techniques. Method: We designed and conducted a systematic literature review on domain-oriented specification techniques. Results: We identified 53 primary studies, populated the classification framework for each study, and summarized our findings per classification aspect. We found many approaches for creating domain models or domain-specific languages. Observations include: (i) most methods are defined incompletely; (ii) none offers methodical support for the use of domain models or domain-specific languages to create other specifications; (iii) there are specification techniques to integrate models in general, but no study offers methodical support for multiple domain models. Conclusion: The results indicate which topics need further research and which can instead be reused to realize our vision on system development. Editor\u27s note: Open Science material was validated by the Journal of Systems and Software Open Science Board

Automatic Generation of Trace Links in Model-driven Software Development

Traceability data provides the knowledge on dependencies and logical relations existing amongst artefacts that are created during software development. In reasoning over traceability data, conclusions can be drawn to increase the quality of software. The paradigm of Model-driven Software Engineering (MDSD) promotes the generation of software out of models. The latter are specified through different modelling languages. In subsequent model transformations, these models are used to generate programming code automatically. Traceability data of the involved artefacts in a MDSD process can be used to increase the software quality in providing the necessary knowledge as described above. Existing traceability solutions in MDSD are based on the integral model mapping of transformation execution to generate traceability data. Yet, these solutions still entail a wide range of open challenges. One challenge is that the collected traceability data does not adhere to a unified formal definition, which leads to poorly integrated traceability data. This aggravates the reasoning over traceability data. Furthermore, these traceability solutions all depend on the existence of a transformation engine. However, not in all cases pertaining to MDSD can a transformation engine be accessed, while taking into account proprietary transformation engines, or manually implemented transformations. In these cases it is not possible to instrument the transformation engine for the sake of generating traceability data, resulting in a lack of traceability data. In this work, we address these shortcomings. In doing so, we propose a generic traceability framework for augmenting arbitrary transformation approaches with a traceability mechanism. To integrate traceability data from different transformation approaches, our approach features a methodology for augmentation possibilities based on a design pattern. The design pattern supplies the engineer with recommendations for designing the traceability mechanism and for modelling traceability data. Additionally, to provide a traceability mechanism for inaccessible transformation engines, we leverage parallel model matching to generate traceability data for arbitrary source and target models. This approach is based on a language-agnostic concept of three similarity measures for matching. To realise the similarity measures, we exploit metamodel matching techniques for graph-based model matching. Finally, we evaluate our approach according to a set of transformations from an SAP business application and the domain of MDSD

An ontological approach to logistics

In today’s global market, the competitiveness of enterprises is strongly dictated by their ability to collaborate with other enterprises. Ontologies enable common understanding of concepts and have been acknowledged as a powerful means to foster collaboration, both within the boundaries of an individual enterprise (intra-enterprise) as outside these boundaries (inter-enterprise). This paper argues that the use of ontologies can be beneficial for enterprise interoperability in the logistics domain, to improve communication and foster knowledge reuse, to facilitate the integration of existing systems and to support the development process of software solutions. Our experience shows that the development of ontologies for logistics is not a trivial task, and guidelines and best practices are necessary in this domain, especially to bridge the gap between theory and practice. On the one hand, proper theoretical and methodological support for ontology engineering is necessary in order to deliver precise, consistent and well-founded solutions to the market. On the other hand, solutions to practical issues should be provided and not take too long to be produced in order not to be detached from the original real market needs. This paper proposes an ontological approach for logistics that balances the trade-off between precision and pragmatism, by combining top-down and bottom-up practices for ontology engineering. From a top-down perspective, we promote the reuse of existing general-purpose (upper) ontologies and specialize them for the purpose of logistics. From a bottom-up perspective, we reuse code lists and classifications that already exist in logistics to support the creation of instances of our upper level concepts. The paper also presents a representative fragment of our core ontology for logistics and identifies areas for further work in ontology engineering for logistics

The Qualitative background of why a DSL knowledge based platform is needed in the context of Sustainability

With reference to Smart Manufacturing and Industry 4.0 in general, a Digital Thread connects the data and processes for smarter products, smarter production, and smarter integrated ecosystems. While the tangible goods (products and production lines) are understood as needing a Digital Twin as an executable model, i.e. an in-silico entity on which to virtually explore design, production, quality, and lifetime maintenance, the immaterial goods like software and analytics artefacts are not yet treated on par. For the new Digital Thread paradigm to enter the mainstream, models need to be coupled with AI, ML and Data Analytics capabilities, to provide an integrated platform for automatic transformations, generations, and analyses that take advantage of the formalized knowledge about the immaterial and material entities. The formalized knowledge needs to include a variety of models together with Domain Specific Languages that use semantic types at their core. The objective of this overall work is to develop a service-oriented Domain Specific Language (DSL) platform for knowledge management (KM-DSL) especially concerning sustainability and risk management, and then apply it in the context of the Digital Thread platform and demonstrators currently under development in the research group. The KM-DSL is the basis for the design of the smart and aligned processes and workflows that will describe and characterize the collaboration of humans and machines in the future advanced production environments. This paper will examine two strands of that work looking at business logic and understanding along with knowledge harvesting that concentrate on two case studies that will underpin future research to create the aforementioned DSL platform for knowledge management