Database Model Generation from Business Rules
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Solution Overview
Problem
Current methods for generating database models from business rules are error-prone and time-consuming, as they fail to distinguish between source and derived information, leading to impractical storage of redundant data.
Innovation Solution
A method that differentiates between definitional and authorization rules within business rules to accurately determine fact types, creating a database model that only stores source information by processing each fact type and its roles, ensuring normalized database structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic generation of database models from business rules is implemented, then time consumption and error rates are reduced, but the ability to distinguish between source and derived information deteriorates
Solution Approach 1:
The patent segments business rules into distinct types (definitional rules and authorization rules) and processes them through separate analytical steps. This segmentation enables the system to automatically distinguish between source information (from authorization rules) and derived information (from definitional rules), resolving the contradiction between automation speed and information distinction precision.
Solution Approach 2:
The patent introduces an intermediary analysis layer that examines business rules to identify their type and extract relevant fact types. This intermediary processing step automatically separates source information from derived information before database model generation, enabling both high productivity through automation and high precision through structured analysis.
2Measurement precision
If business rules are translated manually into software components, then accuracy of information distinction is maintained, but the process becomes error-prone and time-consuming
Solution Approach 1:
The patent implements a self-service approach where the system automatically analyzes business rules, identifies fact types, and generates database models without requiring manual translation. The automated system performs the distinction between source and derived information internally, eliminating the need for human intervention while maintaining accuracy and reducing time consumption.
Solution Approach 2:
The patent replaces the mechanical manual translation process with an automated computational system. By substituting human analysts with an automated rule-based system, the patent eliminates translation errors and time consumption while maintaining the precision needed to distinguish between source and derived information through structured algorithmic analysis.
3Device complexity
If a relational data model is generated from business vocabulary without distinguishing source and derived information, then the generation process is simplified, but the database model becomes impractical due to redundant information storage
Solution Approach 1:
The patent extracts and separates source information from derived information during the database model generation process. By taking out only the source information (authorized provisions) for storage in the database, the system eliminates redundant derived information while maintaining a relatively simple generation process through automated extraction and filtering mechanisms.
Data Source
AI summary
One embodiment of the invention is a method for generating a database model from a set of business rules. For a business rule given as input, an empty list of fact types is created. A determination of whether the business rule is a definitional rule defining that one or more propositions become true upon occurrence of an event is made. If the business rule is a definitional rule, the fact type of each of the propositions is added to the list of fact types. Otherwise, a determination of whether the business rule is an authorization rule for provision of information that comprises one or more authorized provisions of information corresponding to one or more fact types is made. If the business rule is an authorization rule for provision of information, the corresponding fact types are added to the list of fact types. For each fact type in the list of fact types, the fact type having at least one role, the role having a type, if the type of the role is not a lexical type, the type is added to a list of types. The types in the list of types are processed and the fact types in the list of fact types are processed.