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Resultados de búsqueda para Model-Driven Development

A methodology to automatically translate user requirements into visualizations: Experimental validation

Context: Information visualization is paramount for the analysis of Big Data. The volume of data requiring interpretation is continuously growing. However, users are usually not experts in information visualization. Thus, defining the visualization that best suits a determined context is a very challenging task for them. Moreover, it is often the case that users do not have a clear idea of what objectives they are building the visualizations for. Consequently, it is possible that graphics are misinterpreted, making wrong decisions that lead to missed opportunities. One of the underlying problems in this process is the lack of methodologies and tools that non-expert users in visualizations can use to define their objectives and visualizations.Objective: The main objectives of this paper are to (i) enable non-expert users in data visualization to communicate their analytical needs with little effort, (ii) generate the visualizations that best fit their requirements, and (iii) evaluate the impact of our proposal with reference to a case study, describing an experiment with 97 non-expert users in data visualization.Methods: We propose a methodology that collects user requirements and semi-automatically creates suitable visualizations. Our proposal covers the whole process, from the definition of requirements to the implementation of visualizations. The methodology has been tested with several groups to measure its effectiveness and perceived usefulness.Results: The experiments increase our confidence about the utility of our methodology. It significantly improves over the case when users face the same problem manually. Specifically: (i) users are allowed to cover more analytical questions, (ii) the visualizations produced are more effective, and (iii) the overall satisfaction of the users is larger.Conclusion: By following our proposal, non-expert users will be able to more effectively express their analytical needs and obtain the set of visualizations that best suits their goals.

Autores: Ana Lavalle / Alejandro Maté / Juan Trujillo / Miguel A. Teruel / Stefano Rizzi / 
Palabras Clave: Big Data analytics - data visualization - Experimental validation - Model-Driven Development - requirements engineering

CEPchain: A graphical model-driven solution for integrating complex event processing and blockchain (Abstract)

Blockchain provides an immutable distributed ledger for storing transactions. One of the challenges of blockchain is the particular processing of dynamic queries due to accumulating costs. Complex Event Processing (CEP) provides efficient and effective support for this in a way, however, that is difficult to integrate with blockchain. This paper addresses the research challenges of integrating blockchain with CEP. More specifically, we envision an effective development environment in which (i) event-driven smart contracts are modeled in a graphical way, which are, in turn, (ii) automatically transformed into complementary code that is deployed in both a CEP engine and a blockchain network, and then (iii) executed on off-chain CEP applications which, connected to different data sources and sinks, automatically invoke smart contracts when event pattern conditions are met. We follow a classic systems engineering approach for defining the concepts of our system, called CEPchain, which addresses the described requirements. CEPchain was evaluated using a real-world case study for vaccine delivery, which requires an unbroken cold chain. The results demonstrate that our approach can be applied without requiring experts on event processing and smart contract languages. Our contribution simplifies the design of integrated CEP and blockchain functionality by hiding implementation details and supporting efficient deployment.

Autores: Juan Boubeta-Puig / Jesús Rosa-Bilbao / Jan Mendling / 
Palabras Clave: "Supply Chain" - Blockchain - Complex Event Processing - Graphical modeling tool - Model-Driven Development - Smart Contract

Model-driven system-level validation and verification on the space software domain

The development process of on-board software applications can benefit from model-driven engineering techniques. Model validation and model transformations can be applied to drive the activities of specification, requirements definition, and system-level validation and verification according to the space software engineering standards ECSS-E-ST-40 and ECSS-Q-ST-80. This paper presents a model-driven approach to completing these activities by avoiding inconsistencies between the documents that support them and providing the ability to automatically generate the system-level validation tests that are run on the Ground Support Equipment and the matrices required to complete the software verification. A demonstrator of the approach has been built using as a proof of concept a subset of the functionality of the software of the control unit of the Energetic Particle Detector instrument on-board Solar Orbiter.

Autores: Aaron Montalvo / Pablo Parra / Óscar Rodríguez Polo / Alberto Carrasco / Antonio Da Silva / Agustín Martínez / Sebastián Sánchez / 
Palabras Clave: ECSS standards - Model-Driven Development - Space Software - Validation and Verification

Engineering human-in-the-loop cyber-physical systems

Context: Cyber-Physical Systems (CPSs) are gradually and widely introducing autonomous capabilities into everything. However, human participation is required to accomplish tasks that are better performed with humans (often called human-in-the-loop). In this way, human-in-the-loop solutions have the potential to handle complex tasks in unstructured environments, by combining the cognitive skills of humans with autonomous systems behaviors.Objective: The objective of this paper is to provide appropriate techniques and methods to help designers analyze and design human-in-the-loop solutions. These solutions require interactions that engage the human, provide natural and understandable collaboration, and avoid disturbing the human in order to improve human experience.Method: We have analyzed several works that identified different requirements and critical factors that are relevant to the design of human-in-the-loop solutions. Based on these works, we have defined a set of design principles that are used to build our proposal. Fast-prototyping techniques have been applied to simulate the designed human-in-the-loop solutions and validate them.Results: We have identified the technological challenges of designing human-in-the-loop CPSs and have provided a method that helps designers to identify and specify how the human and the system should work together, focusing on the control strategies and interactions required.Conclusions: The use of our approach facilitates the design of human-in-the-loop solutions. Our method is practical at earlier stages of the software life cycle since it allows domain experts to focus on the problem and not on the solution.

Autores: Miriam Gil / Manoli Albert / Joan Fons / Vicente Pelechano / 
Palabras Clave: Cyber-Physical Systems - Human in the Loop - Human-System interactions - Model-Driven Development

Integrating Complex Event Processing and Machine Learning: an Intelligent Architecture for Detecting IoT Security Attacks (Abstract)

The Internet of Things (IoT) is growing globally at a fast pace. However, the increase in IoT devices has brought with it the challenge of promptly detecting and combating the cybersecurity threats that target them. To deal with this problem, we propose an intelligent architecture that integrates Complex Event Processing (CEP) technology and the Machine Learning (ML) paradigm in order to detect different types of IoT security attacks in real time. In particular, such an architecture is capable of easily managing event patterns whose conditions depend on values obtained by ML algorithms. Additionally, a model-driven graphical tool for security attack pattern definition and automatic code generation is provided, hiding all the complexity derived from implementation details from domain experts. The proposed architecture has been applied in the case of a healthcare IoT network to validate its ability to detect attacks made by malicious devices. The results obtained demonstrate that this architecture satisfactorily fulfils its objectives.

Autores: José Roldán-Gómez / Juan Boubeta-Puig / José Luis Martínez / Guadalupe Ortiz / 
Palabras Clave: Complex Event Processing - Internet of Things - Machine Learning - Model-Driven Development - Security attack - Software Architecture

A Platform-Aware Model-Driven Embedded Software Engineering Process Based on Annotated Analysis Models

Artículo ya publicado.Título: «A Platform-Aware Model-Driven Embedded Software Engineering Process Based on Annotated Analysis Models»Autores: Pablo Parra, Óscar R. Polo, Javier Fernández, Antonio Da Silva, Sebastián Sánchez y Agustín MartínezRevista: IEEE Transactions on Emerging Topics in ComputingFecha de publicación: 17 de agosto de 2018DOI: 10.1109/TETC.2018.2866024Factor de Impacto 2017: 3,626Cuartil: Q1Referencia:

Autores: Pablo Parra / Oscar R. Polo / Javier Fernandez / Antonio Da Silva / Sebastián Sánchez / Agustín Martínez / 
Palabras Clave: Component-based Software Engineering - Model-Driven Development - On-board Software - Schedulability Analysis

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