No/Low-code platforms have become a trendy topic recently. Approaches to building an internal editor’s architecture may differ, influencing platform functionality. MobiDev explores three main approaches to building an internal architecture with No/ Low-code platforms.
1. Editor -> code + meta information -> code
This approach generates the resulting code on the go and allows users to pick and customize certain elements through a visual editor. As the customization of a certain element is done – it automatically changes the codebase to keep it up to date with the changes. In the vast majority of cases, this approach is used precisely as the basis for editing web pages: code becomes an HTML page with its visualization.
2. Editor -> JSON -> code
As an intermediate data format, JSON can be replaced by any other format. Although it provides some advantages. The editor uses an intermediate data model, so it won’t have restrictions on the UI part, and a full-fledged drag and drop functionality of various UI components can be implemented. JSON and XML are convenient in that they can complete serialization or deserialization of UI code, regardless of the technology for which the final code is generated.
3. Editor -> intermediate components -> code
The third approach to implementing the architecture (Editor -> intermediate components -> code), at first glance, does not differ much from the previous one. However, the essential difference is that the code responsible for these components is not generated, being that it is a part of the library that’s connected to the application and is working as an external plug-in resource of the program.
More detailed information about the technologies behind No/Low-code platforms and solutions can be found at:
https://mobidev.biz/blog/technologies-behind-no-code-low-code-platforms-how-to-build-your-own
MobiDev is an international software engineering company with offices in Poland and Ukraine. The company is focused on helping visionaries create their products. MobiDev invests into technology research and has years of experience building AI-powered solutions, implementing machine learning, augmented reality, and IoT.
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