Fiacre: an Intermediate Language for Model Verification in the Topcased Environment

International audienceFiacre was designed in the framework of the TOPCASED project dealing with model-driven engineering and gathering numerous partners, from both industry and academics. Therefore, Fiacre is designed both as the target language of model transformation engines from various models such as SDL, UML, AADL, and as the source language of compilers into the targeted verification toolboxes, namely CADP and Tina in the first step. In this paper, we present the Fiacre language. Then transformations from AADL to Fiacre are illustrated on a small example

Interoperability between a dynamic reliability modeling and a Systems Engineering process – Principles and Case Study

International audienceIndustrial systems are often large, and complex, in terms of structure, dynamic interactions between subsystems and components, dynamic operational environment, ageing, etc. The dynamic reliability approach is a convenient framework to model the behavior of such systems. However, there is a price to pay, e.g. in terms of amount of data, size of state graphs, volume of reliability calculations, and combination of various engineering activities. A sound Systems Engineering process, benefiting from the improvement of most recent tools, may be a fruitful approach to decrease these difficulties. Although feasibility demonstrations have been done for conventional, static, approaches of dependability, interoperability between dynamic reliability modeling and Systems Engineering has not the same maturity level. The article explains how, on the basis of Systems Engineering (SE) process definitions, a Meta-model defines a framework for integrating the safety into SE processes. It supports a "hub automaton", that is the key element for interoperability with the tools and activities required for a dynamic reliability assessment. The case study is the dynamic assessment of availability of a feed-water control system in a power plant steam generator, presented in previous articles

Achieving non-intrusive interoperability between models for involving users in modeling tasks

[EN] Model-Driven Development (MDD) promotes models as the cornerstone in the software development process, thereby displacing source code as the development process's main feature. Although this model-centric schema claims advantages over traditional software development (e.g., the code could be automatically generated from the models), it does not have the level of adoption that has been expected. The literature review reveals a broad agreement in the fact that end-users may develop and adapt systems themselves but the complexity in modeling standards and the lack of modeling skills prevents their active involvement in modeling tasks of existing MDD processes. To overcome this, end-users should be provided with different modeling languages that use concepts, which fit their particular skills, context and needs. This challenge is the main goal of this thesis, which is addressed by combining the End-user Development and the Model-Driven Development fields. This work starts with the involvement of end-users into the modeling tasks using a tool-supported visual modeling language that allows end-users to select and customize system features of pervasive systems using closer concepts for them. Afterwards, this thesis shows the necessity of enriching existing MDD processes for supporting the development of a new generation of software systems (e.g., smart health) that require expertise in a variety of domains. Consequently, different types of users (e.g., scientists, engineers and end-users) must actively participate in the description of model fragments that depend on their expertise using a different modeling language. Thus, users are able to collaborate to obtain a unified system description. At this point, it becomes necessary to provide mechanisms that transforms models fragments from one modeling language to another, delimits which model fragments are described by a different user, and integrates those model fragments. To provide this, the presented approach encompasses variability management in a novel way to enable collaborative modeling by supporting both the selection of model fragments of the system that may be described using a different modeling language, and the integration of those model fragments once they are described. Furthermore, interoperability mechanisms bridge two different modeling languages in a non-intrusive way with the structure of models by transforming the description of gaps. Thus, our proposal could enrich models of existing MDD processes with model fragments that have been described using a different modeling language, which could make users feel confident to adopt models for describing domain-specific content and could help to adopt MDD processes. The proposal has been validated in three case studies from different levels of complexity and domains: smart home systems, web information systems, and biomechanical protocols. The results have proven the applicability and feasibility of our approach to actively involve different types of users (end- users with software professionals, domain experts with software development experts, and doctors with biomedical engineers, respectively) in model descriptions of existing MDD processes using a different modeling language.[ES] En el Desarrollo de Software Dirigido por Modelos (DSDM) los modelos son la piedra angular del proceso de desarrollo de software, desplazando así al código fuente como artefacto principal. Aunque este enfoque centrado en modelos ofrece ventajas sobre el desarrollo de software tradicional (por ejemplo, la generación de código de forma automática a partir de los modelos) no tiene el nivel de adopción esperado. La literatura científica revela un amplio acuerdo en el hecho de que los usuarios finales puedan ellos mismos desarrollar y adaptar los sistemas pero la complejidad de los estándares de modelado y la carencia de habilidades de modelado impide su participación activa en procesos DSDM existentes. Para lograrlo, los usuarios finales deben disponer de lenguajes de modelado diferentes con conceptos adaptados a sus habilidades, contexto y necesidades. Este desafío es el objetivo principal de esta tesis que se aborda combinando las ideas del desarrollo orientado al usuario final y el DSDM. Este trabajo comienza involucrando usuarios finales en tareas de modelado con una herramienta que les proporciona un lenguaje de modelado visual para seleccionar y personalizar características de un sistema pervasivo utilizando conceptos familiares para ellos. Después, esta tesis motiva la necesidad de enriquecer procesos de DSDM existentes para soportar el desarrollo de una nueva generación de sistemas software (por ejemplo, salud inteligente) que requieren conocimientos especializados en una variedad de dominios. Consecuentemente, diferentes tipos de usuarios (por ejemplo, científicos, ingenieros y usuarios finales) deben participar activamente en la descripción de fragmentos de modelos que dependen de su experiencia utilizando un lenguaje de modelado diferente. De este modo, los usuarios pueden colaborar para obtener una descripción del sistema unificada. En este punto, es necesario proporcionar mecanismos que transformen e integren los fragmentos de un lenguaje de modelado a otro y delimiten qué fragmentos se describen por un usuario diferente. Para proporcionar esto, la propuesta presentada utiliza la gestión de variabilidad de forma novedosa para permitir modelado colaborativo seleccionando fragmentos de un modelo del sistema que pueden ser descritos utilizando un lenguaje de modelado diferente y, la integración de esos fragmentos una vez que hayan sido descritos. Además, la propuesta utiliza mecanismos de interoperabilidad para conectar dos lenguajes de modelado diferentes transformando la descripción de los fragmentos de una manera no invasiva con su estructura. Por tanto, nuestra propuesta puede enriquecer los modelos de procesos DSDM existentes con fragmentos de modelos que han sido descritos con un lenguaje diferente y esto, podría hacer que los usuarios se sientan seguros al adoptar modelos para describir contenido de dominio específico y podría ayudar a adoptar procesos DSDM. La propuesta ha sido validada en tres casos de estudio con diferentes niveles de complejidad y dominios: sistemas para el hogar inteligente, sistemas de información web y protocolos biomecánicos. Los resultados han demostrado la aplicabilidad y viabilidad de nuestra propuesta para involucrar diferentes tipos de usuarios (usuarios finales con profesionales de software, expertos en el dominio con expertos en desarrollo de software y, médicos con ingenieros biomédicos, respectivamente) en descripciones de modelos de procesos DSDM existentes utilizando un lenguaje de modelado diferente.[CA] En el Desenvolupament de Programari Dirigit per Models (DPDM) els models són la pedra angular del procés de desenvolupament de programari, desplaçant així al codi font com a artefacte principal. Encara que aquest enfocament centrat en models ofereix avantatges sobre el desenvolupament de programari tradicional (per exemple, la generació de codi de forma automàtica a partir dels models) no té el nivell d'adopció esperat. La literatura científica revela un ampli acord en el fet que els usuaris finals puguen ells mateixos desenvolupar i adaptar els sistemes però la complexitat dels estàndards de modelatge i la falta d'habilitats de modelatge impedeix la seua participació activa en processos DPDM existents. Per a aconseguir-ho, els usuaris finals han de disposar de llenguatges de modelatge diferents amb conceptes adaptats a les seues habilitats, context i necessitats. Aquest desafiament és l'objectiu principal d'aquesta tesi que s'aborda combinant les idees del desenvolupament orientat a l'usuari final i el DPDM. Aquest treball comença involucrant usuaris finals en tasques de modelatge amb una eina que els proporciona un llenguatge de modelatge visual que permet als usuaris finals seleccionar i personalitzar característiques d'un sistema pervasiu utilitzant conceptes familiars per a ells. Després, aquesta tesi motiva la necessitat d'enriquir processos de DPDM existents per a suportar el desenvolupament d'una nova generació de sistemes programari (per exemple, salut intel¿ligent) que requereixen coneixements especialitzats en una varietat de dominis. Conseqüentment, diferents tipus d'usuaris (per exemple, científics, enginyers i usuaris finals) han de participar activament en la descripció de fragments de models que depenen de la seua experiència utilitzant un llenguatge de modelatge diferent. D'aquesta manera, els usuaris poden col¿laborar per a obtenir una descripció del sistema unificada. En aquest punt, és necessari proporcionar mecanismes que transformen i integren els fragments d'un llenguatge de modelatge a un altre i delimiten quins fragments es descriuen per un usuari diferent. Per a proporcionar açò, la proposta presentada utilitza la gestió de variabilitat de forma nova per a permetre modelatge col.laboratiu seleccionant fragments d'un model del sistema que poden ser descrits utilitzant un llenguatge de modelatge diferent i, la integració d'aqueixos fragments una vegada que hagen sigut descrits. A més, la proposta utilitza mecanismes d'interoperabilitat per a connectar dos llenguatges de modelatge diferents transformant la descripció dels fragments d'una manera no invasiva amb la seua estructura. Per tant, la nostra proposta pot enriquir els models de processos DPDM existents amb fragments de models que han sigut descrits amb un llenguatge diferent i açò, podria fer que els usuaris se senten segurs en adoptar models per a descriure contingut de domini específic i podria ajudar a adoptar processos DPDM. La proposta ha sigut validada en tres casos d'estudi amb diferents nivells de complexitat i dominis: sistemes per a la llar intel¿ligent, sistemes d'informació web i protocols biomecànics. Els resultats han demostrat l'aplicabilitat i viabilitat de la nostra proposta per a involucrar diferents tipus d'usuaris (usuaris finals amb professionals de programari, experts en el domini amb experts en desenvolupament de programari i, metges amb enginyers biomèdics, respectivament) en descripcions de models de processos DPDM existents utilitzant un llenguatge de modelatge diferent.Pérez Pérez, MF. (2015). Achieving non-intrusive interoperability between models for involving users in modeling tasks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/58429TESI

ChatAgri: Exploring Potentials of ChatGPT on Cross-linguistic Agricultural Text Classification

In the era of sustainable smart agriculture, a massive amount of agricultural news text is being posted on the Internet, in which massive agricultural knowledge has been accumulated. In this context, it is urgent to explore effective text classification techniques for users to access the required agricultural knowledge with high efficiency. Mainstream deep learning approaches employing fine-tuning strategies on pre-trained language models (PLMs), have demonstrated remarkable performance gains over the past few years. Nonetheless, these methods still face many drawbacks that are complex to solve, including: 1. Limited agricultural training data due to the expensive-cost and labour-intensive annotation; 2. Poor domain transferability, especially of cross-linguistic ability; 3. Complex and expensive large models deployment.Inspired by the extraordinary success brought by the recent ChatGPT (e.g. GPT-3.5, GPT-4), in this work, we systematically investigate and explore the capability and utilization of ChatGPT applying to the agricultural informatization field. ....(shown in article).... Code has been released on Github https://github.com/albert-jin/agricultural_textual_classification_ChatGPT.Comment: 24 pages,10+figures,46references.Both the first two authors, Biao Zhao and Weiqiang Jin, made equal contributions to this work. Corresponding author: Guang Yan

Efficiently Querying Large-Scale Heterogeneous Models

With the increase in the complexity of software systems, the size and the complexity of underlying models also increases proportionally. In a low-code system, models can be stored in different backend technologies and can be represented in various formats. Tailored high-level query languages are used to query such heterogeneous models, but typically this has a significant impact on performance. Our main aim is to propose optimization strategies that can help to query large models in various formats efficiently. In this paper, we present an approach based on compile-time static analysis and specific query optimizers/translators to improve the performance of complex queries over large-scale heterogeneous models. The proposed approach aims to bring efficiency in terms of query execution time and memory footprint, when compared to the naive query execution for low-code platforms

Compilation of Heterogeneous Models: Motivations and Challenges

International audienceThe widespread use of model driven engineering in the development of software-intensive systems, including high-integrity embedded systems, gave rise to a "Tower of Babel" of modeling languages. System architects may use languages such as OMG SysML and MARTE, SAE AADL or EAST-ADL; control and command engineers tend to use graphical tools such as MathWorks Simulink/Stateflow or Esterel Technologies SCADE, or textual languages such as MathWorks Embedded Matlab; software engineers usually rely on OMG UML; and, of course, many in-house domain specific languages are equally used at any step of the development process. This heterogeneity of modeling formalisms raises several questions on the verification and code generation for systems described using heterogeneous models: How can we ensure consistency across multiple modeling views? How can we generate code, which is optimized with respect to multiple modeling views? How can we ensure model-level verification is consistent with the run-time behavior of the generated executable application?In this position paper we describe the motivations and challenges of analysis and code generation from heterogeneous models when intra-view consistency, optimization and safety are major concerns. We will then introduce Project P 2 and Hi-MoCo 3-respectively FUI and Eurostars-funded collaborative projects tackling the challenges above. This work continues and extends, in a wider context, the work carried out by the Gene-Auto 4 project [1], [2]. Hereby we will present the key elements of Project P and Hi-MoCo, in particular: (i) the philosophy for the identification of safe and minimal practical subsets of input modeling languages; (ii) the overall architecture of the toolsets, the supported analysis techniques and the target languages for code generation; and finally, (iii) the approach to cross-domain qualification for an open-source, community-driven toolset

Ontology-Based Information Sharing in Weakly Structured Environments

Harmelen, F.A.H. van [Promotor]Herzog, O. [Copromotor

NoXperanto: Crowdsourced Polyglot Persistence

This paper proposes NoXperanto , a novel crowdsourcing approach to address querying over data collections managed by polyglot persistence settings. The main contribution of NoXperanto is the ability to solve complex queries involving different data stores by exploiting queries from expert users (i.e. a crowd of database administrators, data engineers, domain experts, etc.), assuming that these users can submit meaningful queries. NoXperanto exploits the results of meaningful queries in order to facilitate the forthcoming query answering processes. In particular, queries results are used to: (i) help non-expert users in using the multi- database environment and (ii) improve performances of the multi-database environment, which not only uses disk and memory resources, but heavily rely on network bandwidth. NoXperanto employs a layer to keep track of the information produced by the crowd modeled as a Property Graph and managed in a Graph Database Management System (GDBMS)