Metadata Framework for Dynamic Enterprise Input Fields
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Solution Overview
Problem
Existing enterprise software applications require time-intensive manual coding to manage input fields, which limits flexibility and scalability in responding to changing business requirements, such as altering field labels, hiding fields, and attaching functional buttons.
Innovation Solution
A computer-implemented method and framework that uses metadata descriptors to define properties and services for input fields, enabling dynamic control of field presentation, attaching functional icons or buttons, and facilitating data population, with a Model View Controller (MVC) design for data passing and a proxy for temporary data storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual coding is used to manage input fields, then customization is possible, but time consumption increases significantly
Solution Approach 1:
The framework performs preliminary actions by pre-defining a comprehensive set of metadata descriptors that capture all possible input field properties and services. This allows the system to automatically generate customized input fields without requiring manual coding at runtime, thus reducing time consumption while maintaining adaptability.
Solution Approach 2:
Instead of manually coding each input field from scratch, the framework uses metadata descriptors as templates to automatically generate and copy standardized field structures. This copying mechanism preserves customization capabilities while dramatically reducing the time required to create input fields.
2Manufacturing precision
If manual coding is used for each input field, then specific requirements can be met, but scalability decreases
Solution Approach 1:
The framework implements universality by creating a single metadata descriptor structure that can serve multiple input fields across different contexts. Each descriptor contains universal properties (field name, label, data type, services) that can be instantiated repeatedly to fulfill specific requirements while maintaining scalability throughout the enterprise application.
Solution Approach 2:
The framework enables scalability through parameter changes by allowing the same input field template to be adapted to different specific requirements by simply modifying metadata descriptor values. This approach maintains manufacturing precision for specific requirements while enabling easy scaling through parameter adjustment rather than structural changes.
3Productivity
If code reuse is implemented through frameworks, then productivity increases, but implementation complexity increases
Solution Approach 1:
The framework reduces implementation complexity through segmentation by dividing the input field management into distinct, manageable metadata descriptors. Each descriptor represents a specific aspect (field properties, services, validation rules), allowing developers to work with individual segments rather than complex monolithic code structures, thus improving productivity without overwhelming complexity.
Data Source
AI summary
Methods and apparatus, including computer program products, for user input in enterprise software application. A method includes displaying a view on a display device, the view including an input field, and enabling a framework that describes properties and services for each business attribute that is bound to the input field, the framework comprising a list of metadata descriptors for the input field.