Validity Logic System for Flexible Data Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional validity logic in data processing environments lacks flexibility and sufficient information to determine data validity, especially when data becomes obsolete or needs to be retired, as it only provides a simple flag indicating usability without considering time or reason for validity.
Innovation Solution
Implementing a system that determines data validity based on user interaction, customizing settings, and programming logic with default value behavior, allowing for validity logic to be applied to customizing entities, enabling data to be marked as valid or invalid by time or artificial categories, and automatically becoming active or inactive based on set dates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a simple flag is used to indicate data usability, then the system is easy to operate, but the validity information is insufficient
Solution Approach 1:
The validity logic is segmented into multiple independent components: validity type (time-based, category-based, or both), validity information (specific dates or categories), and default behavior settings. This segmentation allows the system to provide comprehensive validity information while maintaining operational simplicity through modular configuration.
Solution Approach 2:
The system transitions from a single-dimensional flag approach to a multi-dimensional validity framework by adding time and category dimensions. Data validity is now determined by combinations of validity types, validity information, and default behaviors, providing richer information without significantly increasing operational complexity.
2Device complexity
If conventional flag strategy is used, then the system structure is simple, but flexibility is insufficient
Solution Approach 1:
The validity logic system is designed to be dynamic and adaptable. Users can configure different validity types (time-based, category-based, or both), set custom validity information, and define default behaviors that can be overridden. This dynamic configuration approach provides flexibility without requiring complex system restructuring.
Solution Approach 2:
The system allows flexibility through parameter changes rather than structural changes. By modifying validity type, validity information, and default behavior parameters, the system can adapt to different data validity requirements while maintaining a consistent underlying structure, thus providing versatility without proportionally increasing complexity.
3Reliability
If data is duplicated to maintain different versions, then data validity can be tracked, but storage efficiency decreases
Solution Approach 1:
Instead of duplicating entire data records to track different versions, the system creates a logical copy through validity logic attributes. The same physical data record can be interpreted as valid or invalid based on configured validity rules, eliminating the need for multiple data copies while maintaining reliable validity tracking.
Solution Approach 2:
The validity logic system provides multi-functionality by serving multiple purposes: tracking data validity, managing version control, enabling historical data access, and controlling data processing behavior. This universal approach eliminates the need for separate mechanisms for each function, reducing overall data storage requirements while maintaining reliability.
Data Source
AI summary
Systems and methods are disclosed for providing validity logic. The disclosed systems and methods may include receiving at least one data value, determining validity data corresponding to the received at least one data value, and providing the validity data corresponding to the received at least one data value. Furthermore, the disclosed systems and methods may include receiving at least one data value, receiving validity data corresponding to the received at least one data value, and determining, based on the received validity data, a validity value, the validity value indicating the validity of the received at least one data value.