Customized Schema for Software Application Extensions
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Solution Overview
Problem
Users face difficulties in extending and customizing software applications without coding, as existing methods like code generation and model engines are limited, making it hard to determine which parts of the generated code relate to specific functionalities and requiring full regeneration upon changes, leading to processing delays and portability issues.
Innovation Solution
A method that instantiates a data-centric software application, receives customization input to modify business logic, formulates a representative model, and applies it to a schema to generate a customized schema, extending the application's functionality without requiring users to write code.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users write application extensions themselves, then customization capability is improved, but time requirement and technical knowledge requirement increase
Solution Approach 1:
The patent introduces a code generator as an intermediary tool between the user and the application extension. The user provides customization requirements in natural language or through configuration files, and the code generator automatically produces the corresponding extension code, eliminating the need for users to manually write code while maintaining full customization capability
Solution Approach 2:
The system enables self-service by allowing users to independently create and customize application extensions through the code generator without requiring external assistance from system integrators or IT departments. The automated code generation process empowers users to perform customization tasks that previously required professional expertise
2Ease of operation
If a code generator is implemented, then ease of operation is improved, but ability to determine code-functionality relationship deteriorates
Solution Approach 1:
The patent implements feedback mechanisms that provide users with clear mappings between their customization inputs and the generated code. The system displays how user specifications are translated into extension code, allowing users to verify and understand the relationship between their requirements and the resulting functionality
Solution Approach 2:
The code generator processes customization requirements in modular segments, generating code in discrete, understandable units that correspond to specific user requirements. This segmentation makes it easier for users to trace which parts of the generated code implement which specific functionalities
3Ease of operation
If model engine approach is used, then ease of operation is improved, but processing delay increases when changes are made
Solution Approach 1:
The patent implements a dynamic code generation system that can respond to user changes in real-time. When users modify their customization requirements, the system incrementally updates only the affected portions of the extension code rather than regenerating the entire extension, significantly reducing processing delays while maintaining ease of operation
4Adaptability or versatility
If users create extensions without coding knowledge, then adaptability is improved, but portability deteriorates
Solution Approach 1:
The patent creates a universal extension framework where extensions generated for one user can be easily ported to other users and systems. The code generator produces standardized, platform-independent extension code that maintains consistent functionality across different environments, ensuring portability while preserving customization capability
Data Source
AI summary
The present invention extends to methods, systems, and computer program products for allowing a computer system user to extend the functionality of a data-centric software application. The method includes instantiating the data-centric software application, where the data-centric application has portions of business logic categorized and associated with items of data-centric application functionality defined in a schema. The method includes receiving customization input to customize at least one of the portions of business logic. The method includes formulating a representative model corresponding to at least one of the portions of customized business logic. The method includes applying the representative model to the schema to generate a customized schema that extends the business logic of the data-centric software application. The method includes instantiating the data-centric software application in accordance with the customized schema to customize the functionality of the business logic in the data-centric software application.


