Dynamic Business Data Object Refactoring Engine
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Solution Overview
Problem
Existing business process management (BPM) software faces disruptions and data integrity issues when updating large data sets, as manual updates can cause errors and inconsistencies in production environments, particularly due to the complexity of linking and updating business data objects and their relationships in real-time.
Innovation Solution
A system and method for dynamically refactoring business data object classes, which includes retrieving a business data object, determining a new class key, updating object linkages, and monitoring for errors or inconsistencies, allowing for real-time updates in production environments without manual intervention and ensuring data integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual updates are performed on business data objects in production environments, then data integrity can be maintained through careful verification, but disruptions to the production environment occur during the update process
Solution Approach 1:
The system performs preliminary actions by creating a complete backup of the business data object and its linked data tables before initiating the refactoring process. This preliminary backup ensures that if any issues occur during the update, the original state can be restored, thus maintaining data integrity while allowing continuous production operations.
Solution Approach 2:
The system introduces an intermediary refactoring engine that acts as a mediator between the update process and the production environment. This engine coordinates the refactoring operations, manages transactions, and ensures that updates are applied atomically, preventing disruptions to production while maintaining data integrity through controlled intermediate states.
2Reliability
If business data objects are updated in real-time in production environments, then data consistency can be maintained, but errors and data corruption may occur during the update process
Solution Approach 1:
The system applies beforehand cushioning by implementing comprehensive error handling and validation mechanisms before, during, and after the refactoring process. Transaction logs are created, and validation rules are enforced to detect and prevent data corruption, cushioning the system against potential errors while maintaining real-time data consistency.
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor the refactoring process, validate data integrity constraints, and provide real-time feedback on the status of updates. This feedback loop enables immediate detection and correction of potential data corruption, ensuring data consistency throughout the real-time update process.
3Stability of the object's composition
If multiple linked data tables are updated simultaneously during refactoring, then data relationships can be maintained, but the complexity of managing transactions increases
Solution Approach 1:
The system segments the refactoring process into distinct, manageable transaction units, each handling specific data tables or relationships. This segmentation allows for independent validation and error handling of each segment, reducing the overall complexity of managing simultaneous updates across multiple linked data tables while maintaining data relationships through coordinated transaction commits.
Data Source
AI summary
A system and method for the dynamic refactoring of business data object classes is provided. The system may comprise a refactoring engine configured to interact with a business process management (BPM) environment. The refactoring engine may retrieve a business data object from the BPM environment. The business data object may include various object linkages, such as object attachments, object assignments, and a business data object audit history. Based on a second business data object class, the refactoring engine may refactor the business data object and the various object linkages.