Towards the next generation of reactive model transformations on low-code platforms

Horváth, Benedek; Horváth, Ákos; Wimmer, Manuel

doi:10.1145/3417990.3420199

Cited by 7 publications

(3 citation statements)

References 40 publications

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“…When analysing the possible correlation between foundations and domain we noticed that MDE is spread across the 90% of the domains represented in our primary studies. This is an additional confirmation that MDE is representative of LCD as core foundation across the business domains, from manufacturing (P3 [84]) to social media (P25 [43]) or blockchain-related technologies (P26 [50]). It is interesting to highlight the fact that GUI and visual programming as foundations have a fair presence across multiple domains, too.…”

Section: Core Technologies Versus Domainsmentioning

confidence: 67%

Modelling in low-code development: a multi-vocal systematic review

2022

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In 2014, a new software development approach started to get a foothold: low-code development. Already from its early days, practitioners in software engineering have been showing a rapidly growing interest in low-code development. In 2021 only, the revenue of low-code development technologies reached 13.8 billion USD. Moreover, the business success of low-code development has been sided by a growing interest from the software engineering research community. The model-driven engineering community has shown a particular interest in low-code development due to certain similarities between the two. In this article, we report on the planning, execution, and results of a multi-vocal systematic review on low-code development, with special focus to its relation to model-driven engineering. The review is intended to provide a structured and comprehensive snapshot of low-code development in its peak of inflated expectations technology adoption phase. From an initial set of potentially relevant 720 peer-reviewed publications and 199 grey literature sources, we selected 58 primary studies, which we analysed according to a meticulous data extraction, analysis, and synthesis process. Based on our results, we tend to frame low-code development as a set of methods and/or tools in the context of a broader methodology, often being identified as model-driven engineering.

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Section: Core Technologies Versus Domainsmentioning

confidence: 67%

Modelling in low-code development: a multi-vocal systematic review

2022

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“…Martínez et al (2017) presented a reactive model transformation engine for ATL, which defines a persistent data flow among models to take care of activating only the strictly needed computation in response to updating of source models. Horváth et al (2020) recently proposed multi-tenant and parallel reactive model transformation as new research lines to generate reactive model transformation on a low-code platform. Similar to our approach, these approaches also use continuous re-execution of transformation rules to propagate source model changes.…”

Section: Incremental Change Propagationmentioning

confidence: 99%

Incremental Model Transformation with Epsilon in Model-Driven Engineering

Ghorbani¹,

Sharbaf²,

Zamani³

2022

AIP

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Model-Driven Engineering (MDE) is a software development paradigm that uses models as the main artifacts in the development process. MDE uses model transformations to propagate changes between source and target models. In some development scenarios, target models should be updated based on the evolution of source models. In such cases, it is required to re-execute all transformation rules to update the target model. Incremental execution of transformations, which partially executes the transformation rules, is a solution to this problem. The Epsilon Transformation Language (ETL) is a well-known model transformation language that does not support incremental executions. In this paper, we propose an approach to support the incremental execution of ETL transformations. Our proposal includes a process, as well as a prototype, to propagate changes to the target model. In the proposed approach, all the changes in the source model are detected to identify and re-execute the rules which deal with computing the required elements for updating the target model. We evaluated the correctness and performance of our approach by means of a case study. Compared to the standard ETL, the results are promising regarding the correctness of target models as well as faster execution of the transformation.

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“…Conforme Sahay et al (2020), um dos principais objetivos deste paradigma é lidar com a baixa oferta de desenvolvedores avançados no mercado de trabalho. Profissionais que não têm necessariamente experiência com programação podem ter treinamento na ferramenta baseada em propor o desenvolvimento em low-code e, assim, já se tornam habilitados para a criação de soluções para a indústria em um espaço de tempo relativamente curto (Horváth et al, 2020).…”

Section: Introductionunclassified

ArcGIS em ação: desenvolvendo aplicações com uma plataforma inovadora

Medeiros do Nascimento,

Braga Melo,

Araújo Ferreira

et al. 2024

Div Journ

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O progresso tecnológico constante gerou uma crescente necessidade de adquirir e consumir novas aplicações e foi essa busca que impulsionou a demanda por métodos mais eficientes de desenvolvimento. Low-code é uma abordagem de desenvolvimento rápido de aplicativos que permite a geração automatizada de código por meio de blocos de construção visuais. O ArcGIS Experience Builder é uma poderosa ferramenta low-code para a criação de experiências geoespaciais. O Survey123 é uma ferramenta também integrante do ArcGIS, projetada especificamente para a criação de formulários personalizados. O Sigabem é um projeto que visa auxiliar as pessoas com deficiências no acesso ao transporte público na Região Metropolitana de Recife. Para a concretização desse trabalho, os estudantes utilizaram ambas ferramentas citadas, aproveitando seus recursos. Através do que estava disponibilizado para o projeto, foi possível implementar as funcionalidades idealizadas. Tornou-se notório que os recursos da plataforma ArcGIS continham muito valor e colaboraram para o processo de desenvolvimento das aplicações. É esperado ainda o teste das funcionalidades implementadas com possíveis usuários reais de ambos os sistemas, realizando melhorias conforme for necessário com o propósito de aperfeiçoar o que foi desenvolvido até então.

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Towards the next generation of reactive model transformations on low-code platforms

Cited by 7 publications

References 40 publications

Modelling in low-code development: a multi-vocal systematic review

Modelling in low-code development: a multi-vocal systematic review

Incremental Model Transformation with Epsilon in Model-Driven Engineering

ArcGIS em ação: desenvolvendo aplicações com uma plataforma inovadora

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