894 research outputs found

    Integrating technical debt into MDE

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    The main goal of this work is to evaluate the feasibility to calculate the technical debt (a traditional software quality approach) in a model-driven context through the same tools used by software deve- lopers at work. The SonarQube tool was used, so that the quality check was performed directly on projects created with Eclipse Modeling Frame- work (EMF) instead of traditionals source code projects. In this work, XML was used as the model speci cation language to verify in Sonar- Qube due to the creation of EMF metamodels in XMI (XML Metadata Interchange) and that SonarQube o ers a plugin to assess the XML lan- guage. After this, our work focused on the de nition of model rules as an XSD schema (XML Schema De nition) and the integration between EMF-SonarQube in order that these metrics were directly validated by SonarQube; and subsequently, this tool determined the technical debt that the analyzed EMF models could containF. G, thanks to Colciencias (Colombia) for funding this work through the Colciencias Grant call 512-2010. This work has been supported by the Spanish MICINN PROS-Req (TIN2010-19130-C02-02), the Generalitat Valenciana Project ORCA (PROMETEO/2009/015), the European Commission FP7 Project CaaS (611351), and ERDF structural funds.Giraldo Velásquez, FD.; España Cubillo, S.; Pineda, MA.; Giraldo, WJ.; Pastor López, O. (2014). Integrating technical debt into MDE. CEUR Workshop Proceedings. http://hdl.handle.net/10251/68278

    A framework for evaluating the quality of modelling languages in MDE environments

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    This thesis presents the Multiple Modelling Quality Evaluation Framework method (hereinafter MMQEF), which is a conceptual, methodological, and technological framework for evaluating quality issues in modelling languages and modelling elements by the application of a taxonomic analysis. It derives some analytic procedures that support the detection of quality issues in model-driven projects, such as the suitability of modelling languages, traces between abstraction levels, specification for model transformations, and integration between modelling proposals. MMQEF also suggests metrics to perform analytic procedures based on the classification obtained for the modelling languages and artifacts under evaluation. MMQEF uses a taxonomy that is extracted from the Zachman framework for Information Systems (Zachman, 1987; Sowa and Zachman, 1992), which proposed a visual language to classify elements that are part of an Information System (IS). These elements can be from organizational to technical artifacts. The visual language contains a bi-dimensional matrix for classifying IS elements (generally expressed as models) and a set of seven rules to perform the classification. As an evaluation method, MMQEF defines activities in order to derive quality analytics based on the classification applied on modelling languages and elements. The Zachman framework was chosen because it was one of the first and most precise proposals for a reference architecture for IS, which is recognized by important standards such as the ISO 42010 (612, 2011). This thesis presents the conceptual foundation of the evaluation framework, which is based on the definition of quality for model-driven engineering (MDE). The methodological and technological support of MMQEF is also described. Finally, some validations for MMQEF are reported.Esta tesis presenta el método MMQEF (Multiple Modelling Quality Evaluation Framework), el cual es un marco de trabajo conceptual, metodológico y tecnológico para evaluar aspectos de calidad sobre lenguajes y elementos de modelado mediante la aplicación de análisis taxonómico. El método deriva procedimientos analíticos que soportan la detección de aspectos de calidad en proyectos model-driven tales como: idoneidad de lenguajes de modelado, trazabilidad entre niveles de abstracción, especificación de transformación de modelos, e integración de propuestas de modelado. MMQEF también sugiere métricas para ejecutar procedimientos analíticos basados en la clasificación obtenida para los lenguajes y artefactos de modelado bajo evaluación. MMQEF usa una taxonomía para Sistemas de Información basada en el framework Zachman (Zachman, 1987; Sowa and Zachman, 1992). Dicha taxonomía propone un lenguaje visual para clasificar elementos que hacen parte de un Sistema de Información. Los elementos pueden ser artefactos asociados a niveles desde organizacionales hasta técnicos. El lenguaje visual contiene una matriz bidimensional para clasificar elementos de Sistemas de Información, y un conjunto de siete reglas para ejecutar la clasificación. Como método de evaluación MMEQF define actividades para derivar analíticas de calidad basadas en la clasificación aplicada sobre lenguajes y elementos de modelado. El marco Zachman fue seleccionado debido a que éste fue una de las primeras y más precisas propuestas de arquitectura de referencia para Sistemas de Información, siendo ésto reconocido por destacados estándares como ISO 42010 (612, 2011). Esta tesis presenta los fundamentos conceptuales del método de evaluación basado en el análisis de la definición de calidad en la ingeniería dirigida por modelos (MDE). Posteriormente se describe el soporte metodológico y tecnológico de MMQEF, y finalmente se reportan validaciones.Aquesta tesi presenta el mètode MMQEF (Multiple Modelling Quality Evaluation Framework), el qual és un marc de treball conceptual, metodològic i tecnològic per avaluar aspectes de qualitat sobre llenguatges i elements de modelatge mitjançant l'aplicació d'anàlisi taxonòmic. El mètode deriva procediments analítics que suporten la detecció d'aspectes de qualitat en projectes model-driven com ara: idoneïtat de llenguatges de modelatge, traçabilitat entre nivells d'abstracció, especificació de transformació de models, i integració de propostes de modelatge. MMQEF també suggereix mètriques per executar procediments analítics basats en la classificació obtinguda pels llenguatges i artefactes de mode-lat avaluats. MMQEF fa servir una taxonomia per a Sistemes d'Informació basada en el framework Zachman (Zachman, 1987; Sowa and Zachman, 1992). Aquesta taxonomia proposa un llenguatge visual per classificar elements que fan part d'un Sistema d'Informació. Els elements poden ser artefactes associats a nivells des organitzacionals fins tècnics. El llenguatge visual conté una matriu bidimensional per classificar elements de Sistemes d'Informació, i un conjunt de set regles per executar la classificació. Com a mètode d'avaluació MMEQF defineix activitats per derivar analítiques de qualitat basades en la classificació aplicada sobre llenguatges i elements de modelatge. El marc Zachman va ser seleccionat a causa de que aquest va ser una de les primeres i més precises propostes d'arquitectura de referència per a Sistemes d'Informació, sent això reconegut per destacats estàndards com ISO 42010 (612, 2011). Aquesta tesi presenta els fonaments conceptuals del mètode d'avaluació basat en l'anàlisi de la definició de qualitat en l'enginyeria dirigida per models (MDE). Posteriorment es descriu el suport metodològic i tecnològic de MMQEF, i finalment es reporten validacions.Giraldo Velásquez, FD. (2017). A framework for evaluating the quality of modelling languages in MDE environments [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90628TESI

    Considerations about quality in model-driven engineering

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s11219-016-9350-6The virtue of quality is not itself a subject; it depends on a subject. In the software engineering field, quality means good software products that meet customer expectations, constraints, and requirements. Despite the numerous approaches, methods, descriptive models, and tools, that have been developed, a level of consensus has been reached by software practitioners. However, in the model-driven engineering (MDE) field, which has emerged from software engineering paradigms, quality continues to be a great challenge since the subject is not fully defined. The use of models alone is not enough to manage all of the quality issues at the modeling language level. In this work, we present the current state and some relevant considerations regarding quality in MDE, by identifying current categories in quality conception and by highlighting quality issues in real applications of the model-driven initiatives. We identified 16 categories in the definition of quality in MDE. From this identification, by applying an adaptive sampling approach, we discovered the five most influential authors for the works that propose definitions of quality. These include (in order): the OMG standards (e.g., MDA, UML, MOF, OCL, SysML), the ISO standards for software quality models (e.g., 9126 and 25,000), Krogstie, Lindland, and Moody. We also discovered families of works about quality, i.e., works that belong to the same author or topic. Seventy-three works were found with evidence of the mismatch between the academic/research field of quality evaluation of modeling languages and actual MDE practice in industry. We demonstrate that this field does not currently solve quality issues reported in industrial scenarios. The evidence of the mismatch was grouped in eight categories, four for academic/research evidence and four for industrial reports. These categories were detected based on the scope proposed in each one of the academic/research works and from the questions and issues raised by real practitioners. We then proposed a scenario to illustrate quality issues in a real information system project in which multiple modeling languages were used. For the evaluation of the quality of this MDE scenario, we chose one of the most cited and influential quality frameworks; it was detected from the information obtained in the identification of the categories about quality definition for MDE. We demonstrated that the selected framework falls short in addressing the quality issues. Finally, based on the findings, we derive eight challenges for quality evaluation in MDE projects that current quality initiatives do not address sufficiently.F.G, would like to thank COLCIENCIAS (Colombia) for funding this work through the Colciencias Grant call 512-2010. This work has been supported by the Gene-ralitat Valenciana Project IDEO (PROMETEOII/2014/039), the European Commission FP7 Project CaaS (611351), and ERDF structural funds.Giraldo-Velásquez, FD.; España Cubillo, S.; Pastor López, O.; Giraldo, WJ. (2016). Considerations about quality in model-driven engineering. Software Quality Journal. 1-66. https://doi.org/10.1007/s11219-016-9350-6S166(1985). Iso information processing—documentation symbols and conventions for data, program and system flowcharts, program network charts and system resources charts. ISO 5807:1985(E) (pp. 1–25).(2011). Iso/iec/ieee systems and software engineering – architecture description. 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    The high school redesign initiative: administrators\u27 perspectives

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    The push to redesign America’s failing schools is in high gear. With the ever-changing landscape of the 21st century global economy, students face a demand to be much more highly skilled entering the workforce. The focus of Topnotch School District is to prepare students in the areas of math, science, and communication skills in order to ensure them a competitive position in the job market. The district will design its course of study to engage students and motivate them to stay in school. The Mississippi Department of Education began an initiative called the 21st Century School Redesign in 2006. The focus of this initiative was to prepare students to compete in the global workforce. With outsourcing of jobs to other countries increasing, the competition for jobs is immense. Students who choose not to go to college must obtain the skills necessary to compete for the higher skilled positions available. Those who do choose to attend college must have the skills necessary to be successful also. The Mississippi Department of Education used a competitive grant process to choose 13 school districts in Phase I of the redesign initiative. Phase II of the redesign initiative saw 19 additional school districts brought on board. This study focused on Topnotch School District, which entered the redesign initiative in Phase II. The study was designed to understand the issues of the initiative that the administration team faced in the implementation process. In this study, formal interviews and casual conversations were used along with archival documents to determine the issues faced by building principals, central office personnel, business managers, technology coordinators, and vocational directors during the implementation of the initiative. The results of this study suggest that there is a lack of knowledge of redesign on the part of the administrative team. The results also show that communication throughout the process is crucial to success. Additionally, the system and procedures of reimbursement and asset management were questionable and led to a number of mistakes

    Maintainability and evolvability of control software in machine and plant manufacturing -- An industrial survey

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    Automated Production Systems (aPS) have lifetimes of up to 30-50 years, throughout which the desired products change ever more frequently. This requires flexible, reusable control software that can be easily maintained and evolved. To evaluate selected criteria that are especially relevant for maturity in software maintainability and evolvability of aPS, the approach SWMAT4aPS+ builds on a questionnaire with 52 questions. The three main research questions cover updates of software modules and success factors for both cross-disciplinary development as well as reusable models. This paper presents the evaluation results of 68 companies from machine and plant manufacturing (MPM). Companies providing automation devices and/or engineering tools will be able to identify challenges their customers in MPM face. Validity is ensured through feedback of the participating companies and an analysis of the statistical unambiguousness of the results. From a software or systems engineering point of view, almost all criteria are fulfilled below expectations

    Agile Processes in Software Engineering and Extreme Programming – Workshops

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    This open access book constitutes papers from the 5 research workshops, the poster presentations, as well as two panel discussions which were presented at XP 2021, the 22nd International Conference on Agile Software Development, which was held online during June 14-18, 2021. XP is the premier agile software development conference combining research and practice. It is a unique forum where agile researchers, practitioners, thought leaders, coaches, and trainers get together to present and discuss their most recent innovations, research results, experiences, concerns, challenges, and trends. XP conferences provide an informal environment to learn and trigger discussions and welcome both people new to agile and seasoned agile practitioners. The 18 papers included in this volume were carefully reviewed and selected from overall 37 submissions. They stem from the following workshops: 3rd International Workshop on Agile Transformation 9th International Workshop on Large-Scale Agile Development 1st International Workshop on Agile Sustainability 4th International Workshop on Software-Intensive Business 2nd International Workshop on Agility with Microservices Programmin

    Towards using intelligent techniques to assist software specialists in their tasks

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    L’automatisation et l’intelligence constituent des préoccupations majeures dans le domaine de l’Informatique. Avec l’évolution accrue de l’Intelligence Artificielle, les chercheurs et l’industrie se sont orientés vers l’utilisation des modèles d’apprentissage automatique et d’apprentissage profond pour optimiser les tâches, automatiser les pipelines et construire des systèmes intelligents. Les grandes capacités de l’Intelligence Artificielle ont rendu possible d’imiter et même surpasser l’intelligence humaine dans certains cas aussi bien que d’automatiser les tâches manuelles tout en augmentant la précision, la qualité et l’efficacité. En fait, l’accomplissement de tâches informatiques nécessite des connaissances, une expertise et des compétences bien spécifiques au domaine. Grâce aux puissantes capacités de l’intelligence artificielle, nous pouvons déduire ces connaissances en utilisant des techniques d’apprentissage automatique et profond appliquées à des données historiques représentant des expériences antérieures. Ceci permettra, éventuellement, d’alléger le fardeau des spécialistes logiciel et de débrider toute la puissance de l’intelligence humaine. Par conséquent, libérer les spécialistes de la corvée et des tâches ordinaires leurs permettra, certainement, de consacrer plus du temps à des activités plus précieuses. En particulier, l’Ingénierie dirigée par les modèles est un sous-domaine de l’informatique qui vise à élever le niveau d’abstraction des langages, d’automatiser la production des applications et de se concentrer davantage sur les spécificités du domaine. Ceci permet de déplacer l’effort mis sur l’implémentation vers un niveau plus élevé axé sur la conception, la prise de décision. Ainsi, ceci permet d’augmenter la qualité, l’efficacité et productivité de la création des applications. La conception des métamodèles est une tâche primordiale dans l’ingénierie dirigée par les modèles. Par conséquent, il est important de maintenir une bonne qualité des métamodèles étant donné qu’ils constituent un artéfact primaire et fondamental. Les mauvais choix de conception, ainsi que les changements conceptuels répétitifs dus à l’évolution permanente des exigences, pourraient dégrader la qualité du métamodèle. En effet, l’accumulation de mauvais choix de conception et la dégradation de la qualité pourraient entraîner des résultats négatifs sur le long terme. Ainsi, la restructuration des métamodèles est une tâche importante qui vise à améliorer et à maintenir une bonne qualité des métamodèles en termes de maintenabilité, réutilisabilité et extensibilité, etc. De plus, la tâche de restructuration des métamodèles est délicate et compliquée, notamment, lorsqu’il s’agit de grands modèles. De là, automatiser ou encore assister les architectes dans cette tâche est très bénéfique et avantageux. Par conséquent, les architectes de métamodèles pourraient se concentrer sur des tâches plus précieuses qui nécessitent de la créativité, de l’intuition et de l’intelligence humaine. Dans ce mémoire, nous proposons une cartographie des tâches qui pourraient être automatisées ou bien améliorées moyennant des techniques d’intelligence artificielle. Ensuite, nous sélectionnons la tâche de métamodélisation et nous essayons d’automatiser le processus de refactoring des métamodèles. A cet égard, nous proposons deux approches différentes: une première approche qui consiste à utiliser un algorithme génétique pour optimiser des critères de qualité et recommander des solutions de refactoring, et une seconde approche qui consiste à définir une spécification d’un métamodèle en entrée, encoder les attributs de qualité et l’absence des design smells comme un ensemble de contraintes et les satisfaire en utilisant Alloy.Automation and intelligence constitute a major preoccupation in the field of software engineering. With the great evolution of Artificial Intelligence, researchers and industry were steered to the use of Machine Learning and Deep Learning models to optimize tasks, automate pipelines, and build intelligent systems. The big capabilities of Artificial Intelligence make it possible to imitate and even outperform human intelligence in some cases as well as to automate manual tasks while rising accuracy, quality, and efficiency. In fact, accomplishing software-related tasks requires specific knowledge and skills. Thanks to the powerful capabilities of Artificial Intelligence, we could infer that expertise from historical experience using machine learning techniques. This would alleviate the burden on software specialists and allow them to focus on valuable tasks. In particular, Model-Driven Engineering is an evolving field that aims to raise the abstraction level of languages and to focus more on domain specificities. This allows shifting the effort put on the implementation and low-level programming to a higher point of view focused on design, architecture, and decision making. Thereby, this will increase the efficiency and productivity of creating applications. For its part, the design of metamodels is a substantial task in Model-Driven Engineering. Accordingly, it is important to maintain a high-level quality of metamodels because they constitute a primary and fundamental artifact. However, the bad design choices as well as the repetitive design modifications, due to the evolution of requirements, could deteriorate the quality of the metamodel. The accumulation of bad design choices and quality degradation could imply negative outcomes in the long term. Thus, refactoring metamodels is a very important task. It aims to improve and maintain good quality characteristics of metamodels such as maintainability, reusability, extendibility, etc. Moreover, the refactoring task of metamodels is complex, especially, when dealing with large designs. Therefore, automating and assisting architects in this task is advantageous since they could focus on more valuable tasks that require human intuition. In this thesis, we propose a cartography of the potential tasks that we could either automate or improve using Artificial Intelligence techniques. Then, we select the metamodeling task and we tackle the problem of metamodel refactoring. We suggest two different approaches: A first approach that consists of using a genetic algorithm to optimize set quality attributes and recommend candidate metamodel refactoring solutions. A second approach based on mathematical logic that consists of defining the specification of an input metamodel, encoding the quality attributes and the absence of smells as a set of constraints and finally satisfying these constraints using Alloy

    Acculturation And Multiculturalism Of Students In Secondary Level Education Programs

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    ABSTRACT Even with the rapid changes that individuals are currently experiencing in the U.S. as a result of its fluctuating economy, increased immigration, and evolutionary technological advances, there is not a curriculum or course requirement that exists for Michigan students in secondary level education programs which specifically addresses the issue of acculturation and multiculturalism. This situation is a present reality. Whether planned or unceremoniously imposed, adjusting to a new way of life can be challenging for many people, and establishing a venue for learning the skills to successfully accomplish this task is imperative. If there is a demonstrated need for curriculum in this area, what objectives would be established, and who should provide the content for those requirements? To answer these questions and frame an effective methods approach for responding to the research questions specifically associated with this study, the Constructivist’s Interpretive Research Paradigm and the Philosophy of Phenomenology have been used to collect, analyze, and interpret pertinent data gathered from an online documentary analysis supported with participants’ answers to interview questions. This research explores implications of having overlooked the need for a comprehensive discourse about the topic introduced, and provides a response that will produce long-term benefits for individuals and society as a whole. In this context, the study was conducted to: 1. Learn what is currently being done to develop/implement curriculum and instruction on the topic of acculturation and multiculturalism; 2. Document and add to the knowledge base relevant findings; and 3. Synthesize information compiled to define and propose effective solutions to the problem introduced. Specifically, when referring to American students, there has to be an acknowledgement that the composition of student body participants has dramatically changed in the U.S. during recent years, and the content of curriculum and instruction presented to them must also be revised in order to accommodate the transformation of our country’s demographic structure. Keywords: Acculturation, multiculturalism, graduates, post-secondary education, the workforce, a qualitative study, employment skills, curriculum, training, needs assessment

    Emerging Business Models for Local Distribution Companies in Ontario

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    Local Distribution Companies (LDCs) have the potential to be leaders in coordinating and stewarding a Sustainable Energy Transition (SET) in Ontario. However, under the current LCD business model structure, LDCs are unable to capture the benefits from sustainable energy and advance a sustainable energy transition. Separately from LDC operations, sustainable energy is disrupting the electricity system through the proliferation of Distributed Energy Resources, Information and Communication Technology occurring Behind the Meter (BTM). The adoption of BTM applications erodes LDC profitability and threatens their existence. The pushing force from an outdated LDC business model compounded with the pulling force from disruptive sustainable technology has created an opportunity for LDCs to innovate their business model in order to adapt to the changing energy paradigm of the 21st century. This paper explores and evaluates seven emerging LDC business models used in Ontario and provides a recommendation of a possible pathway for a viable LDC business model that can leverage sustainable energy while maintaining the electrical grid infrastructure
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