Model-Driven
Development

Model-driven development is the most important principle of low-code development. It’s a software development methodology that allows teams to visually build complex applications through simplified abstractions of pre-built components.

Under the hood, model-driven development simplifies complexity through abstraction and reduces human-process intervention through automation. The model in model-driven development projects is executable in runtime—instead of being interpreted into code. This allows model-driven development to sidestep common ops and quality issues with code-centric projects. 

Compared to other programming methods, model-driven development simplifies and accelerates the development process, which provides the following benefits:

• Developer productivity: Model-driven development accelerates the development process by abstracting and automating many of the routine coding and testing processes required in traditional development.
• Improved quality: Creating models that accurately reflect the requirements and design of the system leads to higher-quality software that meets user requirements.
• Easier maintainability: Model-driven development can improve software maintainability by creating clear and well-structured models designed in a common language and visual representation that everyone can understand.
• Reduced cost: Model-driven development can help to reduce costs by automating many of the routine and tedious tasks while also reducing the risk of introducing errors and inconsistencies that lead to rework.

Low-code exists to streamline development and model-driven development is the most important concept of low-code. 

The right low-code platform should include everything you need to develop applications visually, including drag-and-drop functionality, collaboration channels, automation, and AI. 

Try Mendix for free to experience these tools in a model-driven environment.

Low-code platforms are the best option because they are based on model-driven development best practices. But the platform you select should offer a breadth of other tools and services, including (but not limited to):

• Cloud-native deployment
• Collaborative project spaces
• Easy access to data
• Security, governance, and control
• Robust integration capabilities
• Unlimited openness and extensibility
• Mobile and web application development tools
• AI and process automation
• 24/7 support

Mendix features all the tools teams need to excel with model-driven development. Read more about our Platform features .

In the world of artificial intelligence (AI) software, there are two primary components: Code and data.

A model-driven approach maintains the same data and prioritizes building, coding, and optimizing models to improve performance. The ultimate goal is to improve the code and model architecture. A data-driven AI strategy focuses on improving data quality, consistency, and governance to deliver accurate and organized applications.

The right approach depends on the goal of your application. Many organizations utilize a hybrid approach that equally prioritizes both the model and data.

Test-driven development refers to a bare-bones approach to application development with a focus on short development cycles. Model-driven development can be used in conjunction with a test-driven approach to application development.