10,957 research outputs found

    Towards a Domain Specific Language for a Scene Graph based Robotic World Model

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    Robot world model representations are a vital part of robotic applications. However, there is no support for such representations in model-driven engineering tool chains. This work proposes a novel Domain Specific Language (DSL) for robotic world models that are based on the Robot Scene Graph (RSG) approach. The RSG-DSL can express (a) application specific scene configurations, (b) semantic scene structures and (c) inputs and outputs for the computational entities that are loaded into an instance of a world model.Comment: Presented at DSLRob 2013 (arXiv:cs/1312.5952

    UML-F: A Modeling Language for Object-Oriented Frameworks

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    The paper presents the essential features of a new member of the UML language family that supports working with object-oriented frameworks. This UML extension, called UML-F, allows the explicit representation of framework variation points. The paper discusses some of the relevant aspects of UML-F, which is based on standard UML extension mechanisms. A case study shows how it can be used to assist framework development. A discussion of additional tools for automating framework implementation and instantiation rounds out the paper.Comment: 22 pages, 10 figure

    Ontology-based patterns for the integration of business processes and enterprise application architectures

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    Increasingly, enterprises are using Service-Oriented Architecture (SOA) as an approach to Enterprise Application Integration (EAI). SOA has the potential to bridge the gap between business and technology and to improve the reuse of existing applications and the interoperability with new ones. In addition to service architecture descriptions, architecture abstractions like patterns and styles capture design knowledge and allow the reuse of successfully applied designs, thus improving the quality of software. Knowledge gained from integration projects can be captured to build a repository of semantically enriched, experience-based solutions. Business patterns identify the interaction and structure between users, business processes, and data. Specific integration and composition patterns at a more technical level address enterprise application integration and capture reliable architecture solutions. We use an ontology-based approach to capture architecture and process patterns. Ontology techniques for pattern definition, extension and composition are developed and their applicability in business process-driven application integration is demonstrated

    Statistical Model Checking of e-Motions Domain-Specific Modeling Languages

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    Domain experts may use novel tools that allow them to de- sign and model their systems in a notation very close to the domain problem. However, the use of tools for the statistical analysis of stochas- tic systems requires software engineers to carefully specify such systems in low level and specific languages. In this work we line up both sce- narios, specific domain modeling and statistical analysis. Specifically, we have extended the e-Motions system, a framework to develop real-time domain-specific languages where the behavior is specified in a natural way by in-place transformation rules, to support the statistical analysis of systems defined using it. We discuss how restricted e-Motions sys- tems are used to produce Maude corresponding specifications, using a model transformation from e-Motions to Maude, which comply with the restrictions of the VeStA tool, and which can therefore be used to per- form statistical analysis on the stochastic systems thus generated. We illustrate our approach with a very simple messaging distributed system.Universidad de Málaga Campus de Excelencia Internacional Andalucía Tech. Research Project TIN2014-52034-R an

    Conditional Random Field Autoencoders for Unsupervised Structured Prediction

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    We introduce a framework for unsupervised learning of structured predictors with overlapping, global features. Each input's latent representation is predicted conditional on the observable data using a feature-rich conditional random field. Then a reconstruction of the input is (re)generated, conditional on the latent structure, using models for which maximum likelihood estimation has a closed-form. Our autoencoder formulation enables efficient learning without making unrealistic independence assumptions or restricting the kinds of features that can be used. We illustrate insightful connections to traditional autoencoders, posterior regularization and multi-view learning. We show competitive results with instantiations of the model for two canonical NLP tasks: part-of-speech induction and bitext word alignment, and show that training our model can be substantially more efficient than comparable feature-rich baselines

    Applying MDE tools to defining domain specific languages for model management

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    In the model driven engineering (MDE), modeling languages play a central role. They range from the most generic languages such as UML, to more individual ones, called domain-specific modeling languages (DSML). These languages are used to create and manage models and must accompany them throughout their life cycle and evolution. In this paper we propose a domain-specific language for model management, to facilitate the user's task, developed with techniques and tools used in the MDE paradigm.Fil: Pérez, Gabriela. Universidad Nacional de la Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; ArgentinaFil: Irazábal, Jerónimo. Universidad Nacional de la Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pons, Claudia Fabiana. Universidad Nacional de la Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Giandini, Roxana Silvia. Universidad Nacional de la Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; Argentin

    A UML/OCL framework for the analysis of fraph transformation rules

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    In this paper we present an approach for the analysis of graph transformation rules based on an intermediate OCL representation. We translate different rule semantics into OCL, together with the properties of interest (like rule applicability, conflicts or independence). The intermediate representation serves three purposes: (i) it allows the seamless integration of graph transformation rules with the MOF and OCL standards, and enables taking the meta-model and its OCL constraints (i.e. well-formedness rules) into account when verifying the correctness of the rules; (ii) it permits the interoperability of graph transformation concepts with a number of standards-based model-driven development tools; and (iii) it makes available a plethora of OCL tools to actually perform the rule analysis. This approach is especially useful to analyse the operational semantics of Domain Specific Visual Languages. We have automated these ideas by providing designers with tools for the graphical specification and analysis of graph transformation rules, including a backannotation mechanism that presents the analysis results in terms of the original language notation
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