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Model Transform Tools

Model Transform Tools (MTT) is a system that helps create things like API specifications more easily by using one central, well-organized model. This approach saves time and money, ensures consistent results, and follows industry best practices. The tool works with both local and GitHub projects and can be used as a web service or run in a container like Docker. It’s also flexible, meaning you can add new features to work with different tools and standards.

Deep Dive Podcast

A podcast style discussion of the Model Transform Tools. Ideal if you prefer to listen to a description of the MTT.

Benefits

Exposing APIs (Application Programming Interfaces) for your business services offers significant strategic, operational, and technical benefits.

But designing, implementing and maintaining usable and robust APIs is hard and expensive.

API Generation's Model Transform Tools (MTT) solves these problems and significantly reduces costs and improves quality. It doe by generating API specifications and a range of other key development products from a graphical representation of the information you want to share.

This provides the following benefits:

  • Define once, generate many: Defining the business information in a structured but output agnostic model allows the generation of many outputs. The most common outputs are API specifications, such as OpenAPI, GraphQL and Protobuf. However, there are many other possibilities such as documentation using the Markdown standard, custom data standards, etc.
  • Improve efficiency: The define-once, generate-many principle means that, by only having to invest in producing and maintaining the information models, API and other development costs and times can be significantly reduced.
  • Incorporate best practice: The generators incorporate best practice and any local standards. Defining and implementing these rules is done once; resulting in rigour and consistency across all the generated artefacts.
  • Democratise the development process: The use of standard UML diagrams, which are quick to learn how to read, enable a wide set of skills and experience to be involved in the model's development and review. This leads to more robust and enduring models and hence generated outputs.
  • Provide technology independence: Using a model to generating specifications, rather than code, allows greater freedom to choose the technology to implement APIs, etc. For example, there are many open-source tools that take an API specification as input and generate implementation code in a particular programming language or framework.

Learn

Learn the principles of developing rich information models that can be used, by the API Generation tools, to generate a wide range of artefacts.

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