Centralized Data Validation Framework for Enterprise Applications
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Solution Overview
Problem
Enterprise applications face inefficiencies in data validation and business logic execution when saving data to a shared disk, as each application performs individual validation, leading to redundant processes and potential data integrity issues.
Innovation Solution
A data saving framework with six software interception points (pre-save, entity validation, pre-operation commands, data operation, post-operation commands, and post-save) that provides granular control over data operations and recursive validation, ensuring data integrity by revalidating modified entities during execution, and executing entirely at a server for multiple clients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If each application performs individual data validation before saving to disk, then data integrity can be maintained, but redundant validation processes occur and system efficiency decreases
Solution Approach 1:
The patent merges individual application validation processes into a single centralized validation framework. Multiple applications share common validation logic and rules through a unified validation mechanism, eliminating redundant validation operations while maintaining data integrity across all applications writing to the shared disk.
Solution Approach 2:
The validation framework is designed as a universal system that serves multiple applications simultaneously. A single validation module can validate data from different applications against common business rules and constraints, making the validation process multi-functional and applicable across the entire system rather than requiring separate validation for each application.
2Adaptability or versatility
If individual applications perform separate validation operations, then each application can enforce its own business logic, but the overall process complexity increases
Solution Approach 1:
The validation framework is segmented into distinct interception points (pre-save, entity validation, pre-operation commands, data operation, post-operation commands, and post-save) that can be independently configured. This segmentation allows different business logic to be applied at specific stages without affecting other parts of the validation process, reducing overall complexity while maintaining adaptability.
Solution Approach 2:
The patent introduces an intermediary validation framework that sits between multiple applications and the disk storage. This mediator handles all validation operations centrally, allowing individual applications to interact with a standardized interface while the complex validation logic is managed by the intermediary layer, thus reducing the perceived complexity for each application.
3Reliability
If data validation is performed at multiple interception points with recursive validation, then data integrity is enhanced, but processing time increases
Solution Approach 1:
The framework performs preliminary validation at early interception points (pre-save, entity validation) before data is fully processed and saved. By validating data structure, format, and basic constraints early in the process, the system identifies and corrects issues before they propagate through subsequent processing stages, reducing the need for extensive revalidation later.
Solution Approach 2:
The recursive validation mechanism implements feedback loops where validation results from one interception point inform subsequent validation steps. If validation fails at any point, the framework provides feedback to abort the save operation immediately, preventing wasted processing time on invalid data. Successful validation feedback allows the process to proceed efficiently to the next stage.
Data Source
AI summary
Methods, systems, and computer-readable media for combined saving and validation are disclosed. A particular method includes receiving a command to save changes associated with a change set to a data storage device. Entities of the change set are validated and one or more pre-operation commands are executed on the change set. When a pre-operation command modifies one or more first entities of the change set, the first entities are revalidated. The method also includes executing a data operation based on the change set and executing one or more post-operation commands on the change set. When a post-operation command modifies one or more second entities of the change set, the second entities are re-validated.