An Approach to Flexible Multilevel Modelling

Multilevel modelling approaches tackle issues related to lack of flexibility and mixed levels of abstraction by providing features like deep modelling and linguistic extension. However, the lack of a clear consensus on fundamental concepts of the paradigm has in turn led to lack of common focus in current multilevel modelling tools and their adoption. In this paper, we propose a formal framework, together with its corresponding tools, to tackle these challenges. The approach facilitates definition of flexible multilevel modelling hierarchies by allowing addition and deletion of intermediate abstraction levels in the hierarchies. Moreover, it facilitates separation of concerns by allowing integration of different multilevel modelling hierarchies as different aspects of the system to be modelled. In addition, our approach facilitates reusability of concepts and their behaviour by allowing definition of flexible transformation rules which are applicable to different hierarchies with a variable number of levels. As a proof of concept, a prototype tool and a domain-specific language for the definition of these rules is provided.publishedVersio

Pattern-based refactoring in model-driven engineering

L’ingénierie dirigée par les modèles (IDM) est un paradigme du génie logiciel qui utilise les modèles comme concepts de premier ordre à partir desquels la validation, le code, les tests et la documentation sont dérivés. Ce paradigme met en jeu divers artefacts tels que les modèles, les méta-modèles ou les programmes de transformation des modèles. Dans un contexte industriel, ces artefacts sont de plus en plus complexes. En particulier, leur maintenance demande beaucoup de temps et de ressources. Afin de réduire la complexité des artefacts et le coût de leur maintenance, de nombreux chercheurs se sont intéressés au refactoring de ces artefacts pour améliorer leur qualité. Dans cette thèse, nous proposons d’étudier le refactoring dans l’IDM dans sa globalité, par son application à ces différents artefacts. Dans un premier temps, nous utilisons des patrons de conception spécifiques, comme une connaissance a priori, appliqués aux transformations de modèles comme un véhicule pour le refactoring. Nous procédons d’abord par une phase de détection des patrons de conception avec différentes formes et différents niveaux de complétude. Les occurrences détectées forment ainsi des opportunités de refactoring qui seront exploitées pour aboutir à des formes plus souhaitables et/ou plus complètes de ces patrons de conceptions. Dans le cas d’absence de connaissance a priori, comme les patrons de conception, nous proposons une approche basée sur la programmation génétique, pour apprendre des règles de transformations, capables de détecter des opportunités de refactoring et de les corriger. Comme alternative à la connaissance disponible a priori, l’approche utilise des exemples de paires d’artefacts d’avant et d’après le refactoring, pour ainsi apprendre les règles de refactoring. Nous illustrons cette approche sur le refactoring de modèles.Model-Driven Engineering (MDE) is a software engineering paradigm that uses models as first-class concepts from which validation, code, testing, and documentation are derived. This paradigm involves various artifacts such as models, meta-models, or model transformation programs. In an industrial context, these artifacts are increasingly complex. In particular, their maintenance is time and resources consuming. In order to reduce the complexity of artifacts and the cost of their maintenance, many researchers have been interested in refactoring these artifacts to improve their quality. In this thesis, we propose to study refactoring in MDE holistically, by its application to these different artifacts. First, we use specific design patterns, as an example of prior knowledge, applied to model transformations to enable refactoring. We first proceed with a detecting phase of design patterns, with different forms and levels of completeness. The detected occurrences thus form refactoring opportunities that will be exploited to implement more desirable and/or more complete forms of these design patterns. In the absence of prior knowledge, such as design patterns, we propose an approach based on genetic programming, to learn transformation rules, capable of detecting refactoring opportunities and correcting them. As an alternative to prior knowledge, our approach uses examples of pairs of artifacts before and after refactoring, in order to learn refactoring rules. We illustrate this approach on model refactoring

On the Quality Properties of Model Transformations: Performance and Correctness

The increasing complexity of software due to continuous technological advances has motivated the use of models in the software development process. Initially, models were mainly used as drafts to help developers understand their programs. Later they were used extensively and a new discipline called Model-Driven Engineering (MDE) was born. In the MDE paradigm, aside from the models themselves, model transformations (MT) are garnering interest as they allow the analysis and manipulation of models. Therefore, the performance, scalability and correctness of model transformations have become critical issues and thus they deserve a thorough study. Existing model transformation engines are principally based on sequential and in-memory execution strategies, and hence their capabilities to transform very large models in parallel and in distributed environments are limited. Current tools and languages are not able to cope with models that are not located in a single machine and, even worse, most of them require the model to be in a single file. Moreover, once a model transformation has been written and executed-either sequentially or in parallel-it is necessary to rely on methods, mechanisms, and tools for checking its correctness. In this dissertation, our contribution is twofold. Firstly, we introduce a novel execution platform that permits the parallel execution of both out-place and in-place model transformations, regardless of whether the models fit into a single machine memory or not. This platform can be used as a target for high-level transformation language compilers, so that existing model transformations do not need to be rewritten in another language but only have to be executed more efficiently. Another advantage is that a developer who is familiar with an existing model transformation language does not need to learn a new one. In addition to performance, the correctness of model transformations is an essential aspect that needs to be addressed if MTs are going to be used in realistic industrial settings. Due to the fact that the most popular model transformation languages are rule-based, i.e., the transformations written in those languages comprise rules that define how the model elements are transformed, the second contribution of this thesis is a static approach for locating faulty rules in model transformations. Current approaches able to fully prove correctness-such as model checking techniques-require an unacceptable amount of time and memory. Our approach cannot fully prove correctness but can be very useful for identifying bugs at an early development stage, quickly and cost effectively

Activating Energy Communities for Systemic Change

The speed of energy transition in the Netherlands is low, in contrast to its 2050 climate change target of net-zero emissions. The transition requires 7.5 million households with natural gas connections, to move to renewable energy sources. The main challenge is not technical, many viable options are already available, but social: people will need to be supported to decide and act. In this paper, we identify interventions that could activate change within energy communities, through 19 interviews conducted in March 2021 in Austerlitz, Zeist municipality, The Netherlands. Interview questions were guided by the Capability, Opportunity, Motivation, and Behavioural (COM-B) change model. The model explains factors that affect people’s behaviour. Results indicate that renovation and energy transition are viewed as two separate processes. Austerlitz homeowners are waiting for the government to lead the energy transition process, while they continue to renovate their homes to improve comfort, aesthetics, safety, and convenience. Also, current interventions towards activating households are piecemeal and more focused on creating external opportunities (such as financial support), and barely address the psychological capabilities and motivation factors (belief, attitude, social norm, and perceived behavioural control). To boost psychological capabilities and motivation, we recommend interventions that enhance homeowners’ belief that the energy transition is part of their long-term home renovation plans, for their own benefit, to motivate them to drive the energy transition process. Interventions may include ‘show’ or ‘display’ houses where energy transition was combined with renovations and highlighting inspirational energy transition stories on the municipality website

Co-constructing a new framework for evaluating social innovation in marginalized rural areas

The EU funded H2020 project \u2018Social Innovation in Marginalised Rural Areas\u2019 (SIMRA; www.simra-h2020.eu) has the overall objective of advancing the state-of-the-art in social innovation. This paper outlines the process for co- developing an evaluation framework with stakeholders, drawn from across Europe and the Mediterranean area, in the fields of agriculture, forestry and rural development. Preliminary results show the importance of integrating process and outcome-oriented evaluations, and implementing participatory approaches in evaluation practice. They also raise critical issues related to the comparability of primary data in diverse regional contexts and highlight the need for mixed methods approaches in evaluation

Innovative Concepts and Applications for Smart Water Cities

Smart cities are emerging worldwide, including economic, institutional, social, and technical concepts in interaction with existing infrastructure to achieve sustainability and increase quality of life. Additionally, digitalisation projects in the field of urban water infrastructure (UWI) aim to increase capacity of existing infrastructure to deal with future challenges caused by climate change, growing of urban population, and maintenance. Therefore, efficient and reliable information- and communication technologies (ICT) represent a key factor for the exchange of measurement data (e.g., monitoring environmental parameters) and interconnections between different participants. However, ICT and system-wide management are not yet widely deployed and mainly concentrated on main points in network-based UWI (e.g., combined sewer overflows, inlet point of district meter areas). In this context, especially the Internet of Things (IoT) concepts enables a large-scale implementation of measurement devices even at underground and remote structures, increasing data availability significantly. Following, new possibilities in the management of network-based UWI are emerging. The research aim of this doctoral dissertation is to contribute to the ongoing development of smart water cities by developing innovative concepts in the field of urban drainage and water distribution network including nature-based solutions

Analysing, assessing and safeguarding Alpine open spaces through spatial planning

Alpine open spaces are becoming noticeably scarcer. In the Alps, this applies to the inherently limited area of permanent settlement, which in the case of Tyrol covers only 11.8%. The population is growing in many of the valleys and with it the infrastructure it requires. However, the open spaces at higher altitudes are also being successively fragmented and equipped with infrastructure (e.g. cable cars, hydro-electric plants) or subjected to increasingly intensive use (e.g. with electric mountain bikes). The preservation of open spaces in the Alps began in Bavaria as early as 1972 with the implementation of the Alpine Plan, which established spatial planning objec-tives. The Alpine Plan divided Bavaria's Alpine region into three zones of varying traffic intensity, a true legislative innovation. Zone C was intended for nature conservation, which was still in its infancy at that time, and also aimed to reduce natural Alpine hazards. Primarily, however, this planning initiative was related to the role of the landscape as a setting for recreation in open spaces, i.e. leisure and tourism activities in natural surroundings. Today, there are similar, more or less successful initiatives in all of the German-speaking Alpine states and Switzerland. This publication aims to analyse, compare and describe these initiatives and to critically assess how they are formulated, how they work, and how they are implemented by planners. As the preservation of open spaces is a transnational issue, especially in the Alps, which are intersected by many political borders, we also address the framework provisions of the internationally binding Alpine Convention of 1991 and examine the new EU initiative EUSALP and its potential impact. The focus here, however, is on bringing together approaches for preserving open space for people (local inhabitants and their traditional economic activities, but also visitors) and their natural heritage. We present and critically evaluate present-day spatial planning practices related to Alpine open spaces in the German-speaking Alpine region and in Switzerland, and discuss future options for harmonising approaches across borders