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7 results on '"Plugins"'

1. GIS Open-Source Plugins Development: A 10-Year Bibliometric Analysis on Scientific Literature

Author

Ana Cláudia Teodoro and Lia Duarte

Subjects
Geospatial analysis, 010504 meteorology & atmospheric sciences, mobile GIS, Big data, 0211 other engineering and technologies, 02 engineering and technology, Scientific literature, computer.software_genre, 01 natural sciences, plugins, Software, Information system, web GIS, Plug-in, environmental sciences, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, QE1-996.5, software, business.industry, Geology, Usability, Data science, Field (geography), business, computer, QGIS
Abstract

Background: The advent of Geographical Information Systems (GIS) has changed the way people think and interact with the world. The main objectives of this paper are: (i) to provide an overview of 10 years (2010–2020) regarding the creation/development of GIS open-source applications, and (ii) to evaluate the GIS open-source plugins for environmental science. Methods: In the first objective, we evaluate the publications regarding the development of GIS open-source geospatial software in the last 10 years, considering desktop, web GIS and mobile applications, so that we can analyze the impact of this type of application for different research areas. In the second objective, we analyze the development of GIS open-source applications in the field of environmental sciences (with more focus on QGIS plugins) in the last 10 years and discuss the applicability and usability of these GIS solutions in different environmental domains. A bibliometric analysis was performed using Web of Science database and VOSViewer software. Conclusions: We concluded that, in general, the development of GIS open-source applications has increased in the last 10 years, especially GIS mobile applications, since the big data and Internet of Things (IoT) era, which was expected given the new advanced technologies available in every area, especially in GIS.

Published
2021

2. Research for backup possibilities of websites created in WordPress

Author

Anna Glagkaya and Irina Iegorova

Subjects
World Wide Web, Engineering, CMS, Wordpress, резервне копіювання, плагіни, хмарні сховища, Backup, business.industry, Internet privacy, CMS Wordpress, backup, plugins, cloud services, General Materials Science, business, 004.9
Abstract

У статті проведено дослідження можливостей резервного копіювання сайтів. Виділено способи ручного і автоматичного створення резервних копій для сайтів, розроблених за допомогою CMS Wordpress. Розглянуто особливості резервного копіювання бази даних, файлів, а також тем та плагінів Wordpress. Сформульованi вимоги до періодичності створення резервних копій та кількості резервних копій і їх зберігання, n order to simplify the process of creating and updating sites, content management systems (CMS) are used that provide the ability to jointly create, edit and publish content. One of the most popular CMS is WordPress. This article contains research details for backup possibilities of websites, developed in WordPress. Backup is the one of the essential components of site security. Backup is designed to restore data in case of loss or damage in the original location. Keeping only the development version is not sufficient, because the changes that are made to the site are often not reflected in its original version. Backing up sites involves creating a copy of the site's database or the site's file system. Backup should be performed regularly with frequency which is depending on the frequency of changes made to the site. To automate the backup process, special programs are used, as well as WordPress plugins that will allow to expand its capabilities. The research of the possibilities of backing up Web sites developed with WordPress has made it possible to establish the main advantages and disadvantages of existing plug-ins for these purposes.Existing backup plugins have been analyzed. None of the plugins considered allows to restore the backup from a specific point of time and can't do an incremental backup. The version control strategy is somewhat similar to the backup. Such systems allow you to track changes, and the files that led to the disruption of the site can be undone.Backup-plugin developed with GIT version control system is suggested in the article. Plugin allows to make incremental backup, restore backup from certain point of time and automate the process of backup creation with scheduling

Published
2017

3. Practical detection of CMS plugin conflicts in large plugin sets

Author

Igor Lima, Jeanderson Cândido, and Marcelo d'Amorim

Subjects
Database, CMS, business.industry, Computer science, Plugins, Process (computing), Testing and debugging, 020207 software engineering, Context (language use), 02 engineering and technology, computer.software_genre, Computer Science Applications, Software, 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, Plug-in, Baseline (configuration management), business, computer, Content management system, Information Systems, Web site
Abstract

Context: Content Management Systems (CMS), such as WordPress, are a very popular category of software for creating web sites and blogs. These systems typically build on top of plugin architectures. Unfortunately, it is not uncommon that the combined activation of multiple plugins in a CMS web site will produce unexpected behavior. Conflict-detection techniques exist but they do not scale. Objective: This paper proposes PENA, a technique to detect conflicts in large sets of plugins as those present in plugin market places. Method: PENA takes on input a configuration, consisting of a potentially large set of plugins, and reports on output the offending plugin combinations. PENA uses an iterative divide-and-conquer search to explore the large space of plugin combinations and a staged filtering process to eliminate false alarms. Results: We evaluated PENA with plugins selected from the WordPress official repository and compared its efficiency and accuracy against the technique that checks conflicts in all pairs of plugins. Results show that PENA is 12.4x to 19.6x more efficient than the comparison baseline and can find as many conflicts as it.

Published
2020

4. Software Architectures and Multiple Variability

Author

Philippe Lahire, Mathieu Acher, Philippe Collet, Diversity-centric Software Engineering (DiverSe), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-LANGAGE ET GÉNIE LOGICIEL (IRISA-D4), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe MODALIS, Scalable and Pervasive softwARe and Knowledge Systems (Laboratoire I3S - SPARKS), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Université Nice Sophia Antipolis (1965 - 2019) (UNS), and COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS)

Subjects
Component Based Systems, Resource-oriented architecture, Computer science, Reuse, [INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE], 02 engineering and technology, Video Analysis, Software sizing, 020204 information systems, Architecture, 0202 electrical engineering, electronic engineering, information engineering, Reference architecture, Software product line, Variability Modeling, Software architecture description, business.industry, Software Product Line, Plugins, Software development, 020207 software engineering, Component-based software engineering, Software construction, Configuration Management, business, Software engineering, Software
Abstract

International audience; During the construction of software product lines, variability management is a crucial activity. A large number of software variants must be produced, in most cases, by using extensible architectures. In this chapter, we present the various applications of a set of modular management variability tools (FAMILIAR) for different forms of architecture (component-, service- and plug-in-based), and at different stages of the software life cycle. We discuss the lessons learnt from these studies and present guidelines for resolving recurring problems linked to multiple variability and to software architecture.

Published
2014

5. Extraction and Evolution of Architectural Variability Models in Plugin-based Systems

Author

Philippe Collet, Philippe Merle, Mathieu Acher, Philippe Lahire, Laurence Duchien, Anthony Cleve, Reliable and efficient component based software engineering (TRISKELL), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria), PReCISE Research Centre in Information Systems Engineering (PReCISE), Facultés Universitaires Notre Dame de la Paix (FUNDP), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe MODALIS, Scalable and Pervasive softwARe and Knowledge Systems (Laboratoire I3S - SPARKS), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Adaptive Distributed Applications and Middleware (ADAM), Laboratoire d'Informatique Fondamentale de Lille (LIFL), Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS)-Inria Lille - Nord Europe, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Université Nice Sophia Antipolis (... - 2019) (UNS), and COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS)

Subjects
services, architecture, Computer science, Solution architecture, 02 engineering and technology, [INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE], plugins, components, Architectural pattern, Multilayered architecture, 020204 information systems, evolution, Product lines, 0202 electrical engineering, electronic engineering, information engineering, Software system, Reference architecture, Software architecture description, product line, business.industry, variability, Architecture recovery, Configuration management, Software evolution, 020207 software engineering, reverse engineering, Modeling and Simulation, Software engineering, business, Software architecture, Software, feature model
Abstract

International audience; Variability management is a key issue when building and evolving software-intensive systems, making it possible to extend, confi gure, customize and adapt such systems to customers' needs and speci fic deployment contexts. A wide form of variability can be found in extensible software systems, typically built on top of plugin-based architectures that o ffer a (large) number of con figuration options through plugins. In an ideal world, a software architect should be able to generate a system variant on-demand, corresponding to a particular assembly of plugins. To this end, the variation points and constraints between architectural elements should be properly modeled and maintained over time (i.e., for each version of an architecture). A crucial, yet error-prone and time-consuming, task for a software architect is to build an accurate representation of the variability of an architecture, in order to prevent unsafe architectural variants and reach the highest possible level of flexibility. In this article, we propose a reverse engineering process for producing a variability model (i.e., a feature model) of a plugin-based architecture. We develop automated techniques to extract and combine di fferent variability descriptions, including a hierarchical software architecture model, a plugin dependency model and the software architect knowledge. By computing and reasoning about diff erences between versions of architectural feature models, software architect can control both the variability extraction and evolution processes. The proposed approach has been applied to a representative, large-scale plugin-based system (FraSCAti), considering diff erent versions of its architecture. We report on our experience in this context.

Published
2013

6. ORBISGIS: Geographical Information System Designed by and for Research

Author

Erwan Bocher, Gwendall Petit, Institut de Recherche en Sciences et Techniques de la Ville - FR 2488 (IRSTV), Université de Nantes (UN)-École Centrale de Nantes (ECN)-EC. ARCHIT. NANTES-Université d'Angers (UA)-Université de La Rochelle (ULR)-Centre National de la Recherche Scientifique (CNRS), Projet régional SOGVILLE, wiley, and Université de La Rochelle (ULR)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-Université de Nantes (UN)-École nationale supérieure d'architecture de Nantes (ENSA Nantes)-Université d'Angers (UA)

Subjects
Knowledge management, 010504 meteorology & atmospheric sciences, graphical interface, 02 engineering and technology, Space (commercial competition), 01 natural sciences, Domain (software engineering), Data modeling, plugins, Geographic, 0202 electrical engineering, electronic engineering, information engineering, Information system, perval, Software system, OrbisGIS, 0105 earth and related environmental sciences, Sustainable development, business.industry, [SHS.GEO]Humanities and Social Sciences/Geography, Shared resource, spatial, Geography, Software design, 020201 artificial intelligence & image processing, diachronic, business
Abstract

International audience; At a time when people use more and more geographic information and tools, the management of geographical information in software systems still holds many challenges and motivates researchers from different backgrounds to propose innovative solutions.Representing geographical space beyond our mere perception is key to making relevant decisions, whether it is with respect to sustainable development or to the planning of everyday activities. Designing, sharing and exploiting such representations entails many challenges.This book presents recent software design projects, led in teams, which sometimes have different backgrounds, to address these challenges. It analyzes the specificities of these projects in terms of motivation, data models and analysis methods. Proposals are also put forward to improve resource sharing in this domain.

Published
2013

7. MILXView: A Medical Imaging, Analysis and Visualization Platform

Author

Olivier Salvado, Pierrick Bourgeat, Jurgen Fripp, Neil Burdett, The Australian e-Health Research centre, Royal Brisbane and Women's Hospital, and Hiroshi Takeda

Subjects
VTK, Engineering, computer.software_genre, AEHRC, plugins, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, DICOM, 0302 clinical medicine, Software, Computer graphics (images), Brain mri, Medical imaging, [INFO.INFO-DL]Computer Science [cs]/Digital Libraries [cs.DL], Plug-in, image, WxWidgets, business.industry, CTE, Visualization, ITK, MILXView, 030220 oncology & carcinogenesis, voxel, business, Software engineering, computer
Abstract

International audience; Medical imaging is a vital clinical and research tool that has made significant strides in the last few decades with impressive advances in acquisition technology. However, image analysis and interpretation is still primarily performed manually, and is difficult to automate. In recent years, major advances have been made that allow more automatic image analysis, understanding, and interpretation. In this paper we introduce the 3D medical imaging analysis and visualization platform, MILXView, and present some of its current and potential usage for medical image analysis, understanding and interpretation. The paper describes the design of the plugin architecture of the software application, a general overview of the plugins and the improvements and additions to the latest version of MILXView. As an example the cortical thickness estimation plugin (MILXcte) is described for performing automatic atrophy estimation of brain MRI.

Published
2010

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