Declarative Mapping and Custom Exits for Model Metadata Conversion
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Solution Overview
Problem
Current model integration tools are cumbersome and lack ease of use, requiring manual effort for implementing new integration tools and do not allow developers to influence generated models, making it difficult to convert metadata between different modeling environments like Eclipse and MOIN.
Innovation Solution
A computer-implemented method provides a declarative mapping between metamodels and custom programmable rules to convert metadata between different modeling environments, enabling seamless import and export of models between Eclipse and MOIN, using a combination of declarative mapping and custom exits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual implementation of integration tools is used, then flexibility in creating custom metamodels is improved, but device complexity and effort required increases
Solution Approach 1:
The integration tool is segmented into modular components: a declarative mapping layer that defines relationships between metamodels, and a code generation layer that automatically produces import/export tools. This segmentation allows users to configure custom metamodels through simple mappings without implementing complex integration logic manually.
Solution Approach 2:
The system performs preliminary actions by automatically generating import and export tool code based on the declarative mappings between metamodels. This pre-generation of integration tools eliminates the need for manual implementation while maintaining flexibility, as the generated code can be customized through the declarative mapping configuration.
2Device complexity
If fixed metamodels are used, then device complexity is reduced, but adaptability to changing business logic deteriorates
Solution Approach 1:
The system enables dynamic metamodeling by allowing users to define custom metamodels through declarative mappings that can be configured and modified without changing the underlying framework. This dynamic approach lets the system adapt to changing business logic while maintaining a simple fixed framework structure.
Solution Approach 2:
The system allows parameter changes in metamodel definitions through the declarative mapping language, where users can specify relationships, attributes, and constraints that define custom metamodels. This enables adaptation to different business domains and logic changes without modifying the core framework parameters.
3Manufacturing precision
If custom programmable rules are added to declarative mapping, then manufacturing precision of metadata conversion is improved, but device complexity increases
Solution Approach 1:
The mapping system is segmented into two distinct layers: a declarative mapping layer that handles standard conversions, and a custom programmable rules layer that handles complex transformations. This segmentation allows users to add precision for specific cases through custom rules without making the entire mapping system complex.
Solution Approach 2:
The system introduces an intermediary layer of custom exits that act as mediators between the declarative mapping and the metadata conversion process. These custom exits provide additional precision for complex conversions while maintaining a clean separation from the core declarative mapping system.
4Productivity
If automated code generation is used, then productivity is improved, but ease of operation deteriorates due to lack of developer influence
Solution Approach 1:
The code generation process is made dynamic by allowing developers to influence the generated models through declarative mapping configurations and custom programmable rules. Developers can control aspects like mapping relationships, data type conversions, and validation rules, while the system automatically generates the integration tool code.
Solution Approach 2:
The system incorporates feedback mechanisms that allow developers to review and adjust the generated integration tools based on their requirements. The declarative mapping specifications and custom rules provide feedback loops where developers can refine the generated code to match their operational needs while maintaining high productivity.
Data Source
AI summary
In one embodiment the present invention includes a computer-implemented method of converting first metadata to second metadata using a mapping and custom exits. The metadata is at the M1 level and the mapping is generated based on information at the M2 level. The custom exits provide programmable mapping rules in addition to the mapping. In this manner, metadata created in one modeling environment may be used in another modeling environment.