Schema Relationship Analysis Using Documentation-Code Association Trees
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Solution Overview
Problem
Modifying data in one portion of an application can affect related portions, leading to dirty data or poor performance due to complex business logic relationships, which existing methods struggle to manage effectively.
Innovation Solution
A database schema relationship analysis system that generates association trees from application documentation and source code to identify and suggest modifications to related table entities, using similarity comparison to ensure consistency and provide SQL statements for updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data modification is performed manually in complex business logic relationships, then flexibility and control are maintained, but human error increases and data consistency deteriorates
Solution Approach 1:
The system performs self-service by automatically analyzing database schema relationships, identifying affected table entities, and generating modification suggestions without requiring manual intervention. The system extracts data from application documentation and source code, builds association trees, and autonomously determines the impact of data modifications, thereby maintaining data consistency while reducing operational complexity.
Solution Approach 2:
The system implements feedback by comparing the application documentation table association tree with the source code table association tree to determine a similarity level. This feedback mechanism ensures that modifications suggested by the system are consistent with both the documented requirements and the actual implementation, thereby maintaining data consistency and reliability.
2Reliability
If comprehensive analysis of all data relationships is performed, then data consistency is improved, but system complexity and processing time increase
Solution Approach 1:
The system applies segmentation by dividing the complex analysis task into distinct components: extracting data from application documentation, extracting data from source code, building separate association trees for each, and then comparing them. This segmentation reduces the overall complexity by handling each aspect independently while maintaining comprehensive coverage of data relationships.
Solution Approach 2:
The system uses association trees as intermediary structures to represent and analyze data relationships. These trees serve as mediators between the raw extracted data and the final modification suggestions, simplifying the analysis process while ensuring comprehensive and accurate relationship tracking across the database schema.
3Productivity
If manual identification of associated data is required, then precision in identifying relationships is maintained, but time consumption and productivity decrease
Solution Approach 1:
The system performs preliminary action by pre-building association trees from application documentation and source code before any data modification occurs. This advance preparation enables the system to quickly identify all affected table entities and relationships when a modification is needed, significantly reducing the time required compared to manual identification while maintaining high precision through automated analysis.
Data Source
AI summary
Computer-implemented methods for a database schema relationship analysis system are disclosed herein. Aspects include receiving a table name associated with a modified table entity in a database of an application. Aspects further include generating an application documentation table association tree using data from application documentation of the application. Aspects also include generating a source code table association tree using a set of data from source code of the application. Aspects further include determining a similarity level by comparing the application documentation table association tree and the source code table association tree. Aspects include generating a message that includes a suggestion to modify a table entity associated with the modified table entity using data from the application documentation table association tree and the source code table association tree in response to determining that the similarity level is within a threshold value.