Extending the Real-Time Maude Semantics of Ptolemy to Hierarchical DE Models

This paper extends our Real-Time Maude formalization of the semantics of flat Ptolemy II discrete-event (DE) models to hierarchical models, including modal models. This is a challenging task that requires combining synchronous fixed-point computations with hierarchical structure. The synthesis of a Real-Time Maude verification model from a Ptolemy II DE model, and the formal verification of the synthesized model in Real-Time Maude, have been integrated into Ptolemy II, enabling a model-engineering process that combines the convenience of Ptolemy II DE modeling and simulation with formal verification in Real-Time Maude.Comment: In Proceedings RTRTS 2010, arXiv:1009.398

Raisonnement sur les modèles : détection et isolation d'anomalies dans les systèmes de diagnostic

Dans le cadre du diagnostic à base de Modèle, un ensemble de règles d'inférence est typiquement exploité pour calculer des diagnostics, ceci en utilisant une théorie scientifique et mathématique sur le système à diagnostiquer, ainsi qu'un ensemble d'observations. Contrairement aux hypothèses classiques, les Modèles sont souvent anormaux vis-à-vis d'un ensemble de propriétés requises. Naturellement, cela affecte la qualité des diagnostics [à Airbus]. Une théorie sur la réalité, l'information et la cognition est créé pour redéfinir, dans une perspective basée sur la théorie des modèles, le cadre classique de diagnostic à base de Modèle. Ceci rend possible la formalisation des anomalies et de leur relation avec des propriétés des diagnostics. Avec ce travail et avec l'idée qu'un système de diagnostic implémenté peut être vu comme un objet à diagnostiquer, une théorie de méta-diagnostic est développée, permettant la détection et isolation d'anomalies dans les Modèles des systèmes de diagnostic. Cette théorie est mise en pratique à travers d'un outil, MEDITO; et est testée avec succès à travers un ensemble de problèmes industriels, à Airbus. Comme des différents systèmes de diagnostic Airbus, souffrant d'anomalies variées, peuvent calculer des diagnostics différents, un ensemble de méthodes et outils et développé pour: 1) déterminer la cohérence entre diagnostics et 2) valider et comparer la performance de ces systèmes de diagnostic. Ce travail dépend d'un pont original entre le cadre de diagnostic Airbus et son équivalent académique. Finalement, la théorie de méta-diagnostic est généralisée pour prendre en compte des méta-systèmes autres que des systèmes de diagnostic implémentés.In Model-Based Diagnosis, a set of inference rules is typically used to compute diagnoses using a scientific and mathematical theory about a system under study and some observations. Contrary to the classical hypothesis, it is often the case that these Models are abnormal with respect to a series of required properties, hence affecting the quality of the computed diagnoses with possibly huge economical consequences, in particular at Airbus. A thesis on reality and cognition is firstly used to redefine the classic framework of model-based diagnosis from a formal model-theoretic perspective. This, in turn, enables the formalisation of abnormalities and of their relation with the properties diagnoses. With such material and the idea that an implemented diagnostic system can be seen a real-world artefact to be diagnosed, a theory of meta-diagnosis is developed, enabling the detection and isolation of abnormalities in Models of diagnostic systems and explanation in general. Such theory is then encoded in a tool, called MEDITO, and successfuly tested against Airbus real-world industrial problems. Moreover, as different heterogeneous implemented Airbus diagnostic systems, suffering from distinct abnormalities, may compute different diagnoses, methods and tools are developed for: 1) checking the consistency between subsystem-level diagnoses and 2) validating and comparing the performance of these diagnostic systems. Such work relies on an original bridge between the Airbus framework of diagnosis and its academic counterpart. Finally, meta-diagnosis is generalised to handle meta-systems other than implemented diagnostic systems

The 14th Overture Workshop: Towards Analytical Tool Chains

This report contains the proceedings from the 14th Overture workshop organized in connection with the Formal Methods 2016 symposium. This includes nine papers describing different technological progress in relation to the Overture/VDM tool support and its connection with other tools such as Crescendo, Symphony, INTO-CPS, TASTE and ViennaTalk

Role-Modeling in Round-Trip Engineering for Megamodels

Software is becoming more and more part of our daily life and makes it easier, e.g., in the areas of communication and infrastructure. Model-driven software development forms the basis for the development of software through the use and combination of different models, which serve as central artifacts in the software development process. In this respect, model-driven software development comprises the process from requirement analysis through design to software implementation. This set of models with their relationships to each other forms a so-called megamodel. Due to the overlapping of the models, inconsistencies occur between the models, which must be removed. Therefore, round-trip engineering is a mechanism for synchronizing models and is the foundation for ensuring consistency between models. Most of the current approaches in this area, however, work with outdated batch-oriented transformation mechanisms, which no longer meet the requirements of more complex, long-living, and ever-changing software. In addition, the creation of megamodels is time-consuming and complex, and they represent unmanageable constructs for a single user. The aim of this thesis is to create a megamodel by means of easy-to-learn mechanisms and to achieve its consistency by removing redundancy on the one hand and by incrementally managing consistency relationships on the other hand. In addition, views must be created on the parts of the megamodel to extract them across internal model boundaries. To achieve these goals, the role concept of Kühn in 2014 is used in the context of model-driven software development, which was developed in the Research Training Group 'Role-based Software Infrastructures for continuous-context-sensitive Systems.' A contribution of this work is a role-based single underlying model approach, which enables the generation of views on heterogeneous models. Besides, an approach for the synchronization of different models has been developed, which enables the role-based single underlying model approach to be extended by new models. The combination of these two approaches creates a runtime-adaptive megamodel approach that can be used in model-driven software development. The resulting approaches will be evaluated based on an example from the literature, which covers all areas of the work. In addition, the model synchronization approach will be evaluated in connection with the Transformation Tool Contest Case from 2019

Resilient Perception for Outdoor Unmanned Ground Vehicles

This thesis promotes the development of resilience for perception systems with a focus on Unmanned Ground Vehicles (UGVs) in adverse environmental conditions. Perception is the interpretation of sensor data to produce a representation of the environment that is necessary for subsequent decision making. Long-term autonomy requires perception systems that correctly function in unusual but realistic conditions that will eventually occur during extended missions. State-of-the-art UGV systems can fail when the sensor data are beyond the operational capacity of the perception models. The key to resilient perception system lies in the use of multiple sensor modalities and the pre-selection of appropriate sensor data to minimise the chance of failure. This thesis proposes a framework based on diagnostic principles to evaluate and preselect sensor data prior to interpretation by the perception system. Image-based quality metrics are explored and evaluated experimentally using infrared (IR) and visual cameras onboard a UGV in the presence of smoke and airborne dust. A novel quality metric, Spatial Entropy (SE), is introduced and evaluated. The proposed framework is applied to a state-of-the-art Visual-SLAM algorithm combining visual and IR imaging as a real-world example. An extensive experimental evaluation demonstrates that the framework allows for camera-based localisation that is resilient to a range of low-visibility conditions when compared to other methods that use a single sensor or combine sensor data without selection. The proposed framework allows for a resilient localisation in adverse conditions using image data but also has significant potential to benefit many perception applications. Employing multiple sensing modalities along with pre-selection of appropriate data is a powerful method to create resilient perception systems by anticipating and mitigating errors. The development of such resilient perception systems is a requirement for next-generation outdoor UGVs

A Development Method for the Conceptual Design of Multi-View Modeling Tools with an Emphasis on Consistency Requirements

The main objective of this thesis is to bridge the gap between modeling method experts on the one side and tool developers on the other. More precisely, the focus is on the specification of requirements for multi-view modeling tools. In this regard, the thesis introduces a methodological approach that supports the specification of conceptual designs for multi-view modeling tools in a stepwise manner: the MuVieMoT approach. MuVieMoT utilizes generic multi-view modeling concepts and the model-driven engineering paradigm to establish an overarching specification of multi-view modeling tools with an emphasis on consistency requirements. The approach builds on and extends the theoretical foundation of metamodeling and multi-view modeling: generic multi-view modeling concepts, integrated multi-view modeling approaches, and possibilities for formalized modeling method specifications. Applicability and utility of MuVieMoT are evaluated using an illustrative scenario, therefore specifying a conceptual design for a multi-view modeling tool for the Semantic Object Model enterprise modeling method. The thesis moreover introduces the MuVieMoT modeling environment, enabling the efficient application of the approach as well as the model-driven development of initial multi-view modeling tools based on the conceptual models created with MuVieMoT. Consequently, the approach fosters an intersubjective and unambiguous understanding of the tool requirements between method experts and tool developers

Derivación, Evaluación y Mejora de la Calidad de Arquitecturas Software en el Desarrollo de Líneas de Producto Software Dirigido por Modelos

En los últimos años se han propuesto diferentes aproximaciones para el desarrollo de sistemas altamente complejos. Algunos esfuerzos intentan aplicar la aproximación de Líneas de Producto Software tratando de sacar partido de la reutilización masiva para producir sistemas software que comparten un conjunto común de características. Una Línea de Producto Software (LPS) es un conjunto de sistemas software que comparten un conjunto de características comunes que satisfacen las necesidades específicas de un segmento de mercado particular y que son desarrollados a partir de un conjunto de activos software comunes de un modo preestablecido [6]. El desarrollo de una LPS consta de dos procesos básicos: la Ingeniería del Dominio, donde se establece cuáles son las partes comunes y las variables y se construye un conjunto de activos (product¿s line core assets) como partes de los sistemas software a desarrollar, y la Ingeniería de la Aplicación, donde los core assets son reutilizados sistemáticamente para derivar productos específicos. De este modo se reducen costes y tiempo de desarrollo. En el desarrollo de líneas de producto se presentan dos arquitecturas software que juegan dos roles diferenciados; i) la arquitectura de la línea de producto que da soporte a todas los posibles productos que pueden ser obtenidos a partir de la línea de producto y que cuenta con los mecanismos de variabilidad necesarios para cubrir toda la gama de productos y ii) la arquitectura de producto, que es creada a partir de la arquitectura de la línea de producto ejerciendo los mecanismos de variabilidad, para que esta se adapte a los requisitos del producto en desarrollo. En general, el aseguramiento de la calidad del producto es una actividad crucial para el éxito de la industria del software, pero es, si cabe, más importante cuando se trata del desarrollo de líneas de producto software, dado que la reutilización masiva de core assets hace que los atributos de calidad (propiedades físicas o abstractas de un artefacto software) de los core assets impacten en la calidad de todos los productos de una línea de producto. Este hecho es de especial relevancia cuando tratamos con la arquitectura software, que es el core asset mas critico en el desarrollo de líneas de producto. La arquitectura software es la vía para conseguir el cumplimiento de los requisitos no funcionales de nuestro producto, por lo que asegurar que estos requisitos se cumplen durante el proceso de derivación de la arquitectura es una actividad crítica en el proceso de desarrollo. El desarrollo de líneas de producto va, en la mayoría de los casos, ligada a la aplicación del paradigma de desarrollo dirigido por modelos. El Desarrollo de Software Dirigido por Modelos (DSDM) que promueve el uso de modelos durante a lo largo de todo el proceso de desarrollo de software, permitiendo que estos modelos puedan ser transformados sucesivamente hasta la obtención del producto final. En la literatura no se encuentran propuestas que, de forma completa, sistemática y automatizada, permitan obtener arquitecturas de producto software que cumplan una serie de requisitos de calidad. El presente trabajo de investigación pretende la mejora del contexto anterior proponiendo el método QuaDAI (Quality Driven Architecture Derivation and Improvement), un método de derivación, evaluación y mejora de la calidad de arquitecturas software en el Desarrollo de Líneas de Producto Dirigido por Modelos mediante la definición de un artefacto (el multimodelo) y de un proceso dirigido por transformaciones que permite automatizar un proceso (el de derivación, evaluación y mejora) de por si altamente complejo. Este método va dirigido a empresas de desarrollo de software que utilice el paradigma de LPS y que pretendan introducir técnicas automatizadas de aseguramiento de calidad y para investigadores interesados en el campo de las arquitecturas software, líneas de producto y desarrollo dirigido por modelos.González Huerta, J. (2014). Derivación, Evaluación y Mejora de la Calidad de Arquitecturas Software en el Desarrollo de Líneas de Producto Software Dirigido por Modelos [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/36448TESI

B!SON: A Tool for Open Access Journal Recommendation

Finding a suitable open access journal to publish scientific work is a complex task: Researchers have to navigate a constantly growing number of journals, institutional agreements with publishers, funders’ conditions and the risk of Predatory Publishers. To help with these challenges, we introduce a web-based journal recommendation system called B!SON. It is developed based on a systematic requirements analysis, built on open data, gives publisher-independent recommendations and works across domains. It suggests open access journals based on title, abstract and references provided by the user. The recommendation quality has been evaluated using a large test set of 10,000 articles. Development by two German scientific libraries ensures the longevity of the project