Proposing a Framework for Impact Analysis for Low-Code Development Platforms

Overeem, Michiel; Jansen, Slinger

doi:10.1109/models-c53483.2021.00020

Cited by 10 publications

(2 citation statements)

References 24 publications

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“…Low-code development platform is a trend of rapid development in recent years [5].The so-called low code means that by highly refining the general functions of software, the handwritten code is encapsulated to form functional components, so that developers can arrange them by dragging the components, thus realizing the rapid construction of application software. Compared with the mainstream visual IDE (integrated development environment) for "professional developers" in the current market, the difference of low-code development platform is that it is more widely targeted at groups, mainly "civilian developers" [6]. In recent years, due to the epidemic, many companies' business models and cooperation models are facing severe challenges.…”

Section: Introduction To Low Code Platformmentioning

confidence: 99%

Risk prediction for 10-kV electric power distribution grid with neural network based on low-code platform

Wei,

Guo,

et al. 2023

5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023)

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In order to effectively solve the problems of power system front-end technology diversification and low explicit programming efficiency, a "visual programming" method based on low-code development platform is proposed. This method uses component-based graphical programming tools to build front-end pages, designs data collection forms through the platform, and delivers the collected data to the back-end neural network model for training, so as to predict the fault risk of distribution line units, improve the power enterprise's ability to adapt to demand changes, carry out operation and maintenance more pertinently, and greatly improve the business staff's ability.

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Section: Introduction To Low Code Platformmentioning

confidence: 99%

Risk prediction for 10-kV electric power distribution grid with neural network based on low-code platform

Wei,

Guo,

et al. 2023

5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023)

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“…In our experience, scientific knowledge is often scattered among many articles or hidden within theoretical and abstract contributions. In our work on API management [185], model execution approaches [182], and impact analysis [181] we aimed to synthesize the already available knowledge in a form that serves industry. Artifacts as decision support frameworks and maturity models are well suited to communicate these kinds of results.…”

Section: Partnership Between Academia and Industrymentioning

confidence: 99%

Evolution of Low-Code Platforms

Overeem¹

Self Cite

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Event sourced systems are increasing in popularity because they are reliable, flexible, and scalable. In this article, we point a microscope at a software architecture pattern that is rapidly gaining popularity in industry, but has not received as much attention from the scientific community. We do so through constructivist grounded theory, which proves a suitable qualitative method for extracting architectural knowledge from practitioners. Based on the discussion of 19 event sourced systems we explore the rationale for and the context of the event sourcing pattern. A description of the pattern itself and its relation to other patterns as discussed with practitioners is given. The description itself is grounded in the experience of 25 engineers, making it a reliable source for both new practitioners and scientists. We identify five challenges that practitioners experience: event system evolution, the steep learning curve, lack of available technology, rebuilding projections, and data privacy. For the first challenge of event system evolution, we uncover five tactics and solutions that support practitioners in their design choices when developing evolving event sourced systems: versioned events, weak schema, upcasting, in-place transformation, and copy-and-transform.

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Democratizing Software Development: A Systematic Multivocal Literature Review and Research Agenda on Citizen Development

Binzer

Winkler

2022

Lecture Notes in Business Information Processing

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Proposing a Framework for Impact Analysis for Low-Code Development Platforms

Cited by 10 publications

References 24 publications

Risk prediction for 10-kV electric power distribution grid with neural network based on low-code platform

Risk prediction for 10-kV electric power distribution grid with neural network based on low-code platform

Evolution of Low-Code Platforms

Democratizing Software Development: A Systematic Multivocal Literature Review and Research Agenda on Citizen Development

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