Business Object Model for Deterministic Test Data Generation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional data management tools struggle to create deterministic sets of test business data that adhere to business rules, requiring extensive knowledge of database schemas and business logic, and often lack the capability to modify business data effectively.
Innovation Solution
A business model data management system that identifies business objects within structure documents, locates and executes data management rules from descriptor documents to represent these objects in a database, providing a platform that decouples data management from specific business applications and database schemas, allowing for deterministic data generation based on business rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional data management tools are used to manage business data, then data manipulation can be performed at the table, row, and column level, but the data manager must have strong knowledge of the database schema and business logic
Solution Approach 1:
The patent introduces a business object model as an intermediary layer between the database schema and the user interface. This business object model encapsulates the complexity of database schemas and business logic, providing a simplified abstraction that users can work with without needing to understand the underlying database structure. The business objects serve as mediators that translate user operations into database operations.
Solution Approach 2:
The patent segments the monolithic database schema into discrete business objects with clearly defined structures and relationships. Each business object represents a logical entity (such as Customer, Order, Product) with its own attributes and methods, allowing users to manage data at the business object level rather than dealing with the complex interconnected tables of the underlying database schema.
2Productivity
If automated tools are used to create test data, then data creation can be automated, but the tools create arbitrary data without regard for business rules
Solution Approach 1:
The business object model includes built-in validation logic and business rule enforcement mechanisms that automatically ensure created data complies with business rules. When test data is generated, the business objects themselves validate the data against their defined constraints and relationships, eliminating the need for separate validation steps and ensuring reliability without sacrificing automation efficiency.
Solution Approach 2:
The system incorporates feedback mechanisms where the business object model continuously validates generated data against business rules and provides feedback on compliance. This allows automated test data generation to be both efficient and reliable, as the system can immediately identify and correct violations of business rules during the data creation process.
3Ease of operation
If business applications provide data views, then data can be viewed at the business object level, but the views often do not permit modification of the business data
Solution Approach 1:
The business object model is designed to be multi-functional, serving both as a data representation layer and as a data manipulation layer. The same business objects that provide data views also provide the capability to modify data, eliminating the need for separate read-only view mechanisms. Users can work with business objects directly to both view and modify data according to business rules.
Data Source
AI summary
A business model data management method can include identifying a business object within a business object structure document for a business application, locating data management rules for the identified business object in a business object descriptor document, and executing the located data management rules to represent the identified business object in a database for the business application.