Platform-Independent Model Generation Using Syntactic Metadata
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Solution Overview
Problem
Existing visual modeling environments face challenges in creating platform-independent models that can be interpreted and modified across different tools and versions, leading to inconsistencies and limitations in user interface design and application development.
Innovation Solution
A method and apparatus that generate and interpret platform-independent models using visual modeling tools, incorporating syntactic and semantic descriptions of modeling language entities, allowing for the creation of platform-independent models that can be used across various tools and versions, enabling flexible user interface configurations and efficient application development.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If visual modeling tools are used to create application models, then application development efficiency is improved, but the models become dependent on specific tools and versions
Solution Approach 1:
The patent segments the modeling system into distinct components: a tool-independent model representation layer and tool-specific interface layers. The model is separated into core structural elements that can be independently interpreted by different tools, resolving the contradiction between development efficiency and tool independence.
Solution Approach 2:
The patent introduces an intermediary metadata layer that acts as a bridge between visual modeling tools and the underlying model. This metadata layer contains syntactic and semantic descriptions that enable different tools to interpret the same model without direct tool dependence, allowing both efficient visual modeling and tool independence.
2Adaptability or versatility
If platform-independent models with syntactic descriptions are generated, then compatibility across tools is improved, but model complexity increases
Solution Approach 1:
The patent adds a new dimension to the model by introducing a metadata layer with syntactic and semantic descriptions. This additional dimension enables cross-tool compatibility without fundamentally restructuring the core model, allowing tools to interpret models differently while maintaining the same underlying structure.
Solution Approach 2:
The patent changes the parameters of model entities by adding syntactic and semantic description attributes. These parameter additions provide the necessary information for platform independence while maintaining the original model structure, thus improving compatibility without excessive complexity.
3Adaptability or versatility
If syntactic and semantic descriptions are included in models, then interpretability by different tools is improved, but information processing overhead increases
Solution Approach 1:
The patent applies preliminary action by pre-defining syntactic and semantic descriptions for model entities during model creation. This upfront preparation enables different tools to interpret models without requiring extensive processing or additional metadata generation, reducing overall information processing overhead.
Data Source
AI summary
Methods and apparatus, including computer program products, for supporting a model including descriptions of modeling language entities in a visual modeling environment. A method includes providing a visual modeling tool and modeling language entities being entities of a language of expressing applications designed in a visual modeling language environment, receiving input defining an application in the visual modeling language environment, and generating a platform-independent model of the application based on the input and the modeling language entities. In that method, the modeling language entities have a corresponding syntactic description that can be in accordance with the language, the input defines the application as a selection of the modeling language entities and a configuration of the selection, and the platform-independent model includes the selection, the configuration, and a syntactic description of the modeling language entities in the selection.