Constructing Domain-Specific Component Frameworks through Architecture Refinement

Acceptance rate: 38%International audienceRecently, a plethora of domain-specific component frameworks (DSCF) emerges. Although the current trend emphasizes generative programming methods as cornerstones of software development, they are commonly applied in a costly, ad-hoc fashion. However, we believe that DSCFs share the same subset of concepts and patterns. In this paper we propose two contributions to DSCF development. First, we propose DomainComponents --- a high-level abstraction to capture semantics of domain concepts provided by containers, and we identify patterns facilitating their implementation. Second, we develop a generic framework that automatically generates implementation of DomainComponents semantics, thus addressing domain-specific services with one unified approach. To evaluate benefits of our approach we have conducted several case studies that span different domain-specific challenges

A Three-Tier Approach for Composition of Real-Time Embedded Software Stacks

CORE A.International audienceMany component models and frameworks have been proposed to abstract and capture concerns from Real-Time and Embedded application domains, based on high-level component-based approaches. However, these approaches tend to propose their own fixed-set abstractions and ad-hoc runtime platforms, whereas the current trend emphasizes more flexible solutions, as embedded systems must constantly integrate new functionalities, while preserving performance. In this paper, we present a two-fold contribution addressing this statement. First, we propose to express these concerns in a decoupled way from the commonly accepted structural abstractions inherent to CBSE, and provide a framework to implement them in open and extensible runtime containers. Second, we propose a three-tier approach to composition where application, containers and the underlying operating system are designed using components. Supporting a homogeneous design space allows applying optimization techniques at these three abstraction layers showing that our approach does not impact on performance. In this paper, we focus our evaluation on concerns specific to the field of real-time audio and music applications

Towards an aspect weaving BPEL engine

This position paper proposes the use of dynamic aspects and the visitor design pattern to obtain a highly configurable and extensible BPEL engine. Using these two techniques, the core of this infrastructural software can be customised to meet new requirements and add features such as debugging, execution monitoring, or changing to another Web Service selection policy. Additionally, it can easily be extended to cope with customer-specific BPEL extensions. We propose the use of dynamic aspects not only on the engine itself but also on the workflow in order to tackle the problems of Web Service hot deployment and hot fixes to long running processes. In this way, composing aWeb Service "on-the-fly" means weaving its choreography interface into the workflow

Programming tools for intelligent systems

Les outils de programmation sont des programmes informatiques qui aident les humains à programmer des ordinateurs. Les outils sont de toutes formes et tailles, par exemple les éditeurs, les compilateurs, les débogueurs et les profileurs. Chacun de ces outils facilite une tâche principale dans le flux de travail de programmation qui consomme des ressources cognitives lorsqu’il est effectué manuellement. Dans cette thèse, nous explorons plusieurs outils qui facilitent le processus de construction de systèmes intelligents et qui réduisent l’effort cognitif requis pour concevoir, développer, tester et déployer des systèmes logiciels intelligents. Tout d’abord, nous introduisons un environnement de développement intégré (EDI) pour la programmation d’applications Robot Operating System (ROS), appelé Hatchery (Chapter 2). Deuxièmement, nous décrivons Kotlin∇, un système de langage et de type pour la programmation différenciable, un paradigme émergent dans l’apprentissage automatique (Chapter 3). Troisièmement, nous proposons un nouvel algorithme pour tester automatiquement les programmes différenciables, en nous inspirant des techniques de tests contradictoires et métamorphiques (Chapter 4), et démontrons son efficacité empirique dans le cadre de la régression. Quatrièmement, nous explorons une infrastructure de conteneurs basée sur Docker, qui permet un déploiement reproductible des applications ROS sur la plateforme Duckietown (Chapter 5). Enfin, nous réfléchissons à l’état actuel des outils de programmation pour ces applications et spéculons à quoi pourrait ressembler la programmation de systèmes intelligents à l’avenir (Chapter 6).Programming tools are computer programs which help humans program computers. Tools come in all shapes and forms, from editors and compilers to debuggers and profilers. Each of these tools facilitates a core task in the programming workflow which consumes cognitive resources when performed manually. In this thesis, we explore several tools that facilitate the process of building intelligent systems, and which reduce the cognitive effort required to design, develop, test and deploy intelligent software systems. First, we introduce an integrated development environment (IDE) for programming Robot Operating System (ROS) applications, called Hatchery (Chapter 2). Second, we describe Kotlin∇, a language and type system for differentiable programming, an emerging paradigm in machine learning (Chapter 3). Third, we propose a new algorithm for automatically testing differentiable programs, drawing inspiration from techniques in adversarial and metamorphic testing (Chapter 4), and demonstrate its empirical efficiency in the regression setting. Fourth, we explore a container infrastructure based on Docker, which enables reproducible deployment of ROS applications on the Duckietown platform (Chapter 5). Finally, we reflect on the current state of programming tools for these applications and speculate what intelligent systems programming might look like in the future (Chapter 6)

Developing virtual and augmented reality applications for science, technology, engineering and math education

The Rhode Island IDeA Network of Biomedical Research Excellence Molecular Informatics Core at the University of Rhode Island Information Technology Services Innovative Learning Technologies developed virtual and augmented reality applications to teach concepts in biomedical science, including pharmacology, medicinal chemistry, cell culture and nanotechnology. The apps were developed as full virtual reality/augmented reality and 3D gaming versions, which do not require virtual reality headsets. Development challenges included creating intuitive user interfaces, text-to-voice functionality, visualization of molecules and implementing complex science concepts. In-app quizzes are used to assess the user\u27s understanding of topics, and user feedback was collected for several apps to improve the experience. The apps were positively reviewed by users and are being implemented into the curriculum at the University of Rhode Island

A Big Data Architecture for Digital Twin Creation of Railway Signals Based on Synthetic Data

Industry 5.0 has introduced new possibilities for defining key features of the factories of the future. This trend has transformed traditional industrial production by exploiting Digital Twin (DT) models as virtual representations of physical manufacturing assets. In the railway industry, Digital Twin models offer significant benefits by enabling anticipation of developments in rail systems and subsystems, providing insight into the future performance of physical assets, and allowing testing and prototyping solutions prior to implementation. This paper presents our approach for creating a Digital Twin model in the railway domain. We particularly emphasize the critical role of Big Data in supporting decision-making for railway companies and the importance of data in creating virtual representations of physical objects in railway systems. Our results show that the Digital Twin model of railway switch points, based on synthetic data, accurately represents the behavior of physical railway switches in terms of data points

Album cover art image generation with Generative Adversarial Networks

Generative Adversarial Networks (GANs) were introduced by Goodfellow in 2014, and since then have become popular for constructing generative artificial intelligence models. However, the drawbacks of such networks are numerous, like their longer training times, their sensitivity to hyperparameter tuning, several types of loss and optimization functions and other difficulties like mode collapse. Current applications of GANs include generating photo-realistic human faces, animals and objects. However, I wanted to explore the artistic ability of GANs in more detail, by using existing models and learning from them. This dissertation covers the basics of neural networks and works its way up to the particular aspects of GANs, together with experimentation and modification of existing available models, from least complex to most. The intention is to see if state of the art GANs (specifically StyleGAN2) can generate album art covers and if it is possible to tailor them by genre. This was attempted by first familiarizing myself with 3 existing GANs architectures, including the state of the art StyleGAN2. The StyleGAN2 code was used to train a model with a dataset containing 80K album cover images, then used to style images by picking curated images and mixing their styles

WARP : speeding up the software development process

Estágio realizado na Qimonda Portugal, S. ATese de mestrado integrado. Engenharia Informátca e Computação. Faculdade de Engenharia. Universidade do Porto. 200