Automated Business Rule Pattern Matching for Software Reuse
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Solution Overview
Problem
In model-based software systems, identifying and reusing business rules across various actions is a time-consuming and challenging task due to the complexity of data modeling and the granularity of business logic, making it difficult for design engineers to recognize subsets of business rules that can be reused.
Innovation Solution
A pattern-based approach is employed to identify business rule reuse by forming pattern signatures for each action and scanning for repeated patterns across actions, allowing designers to maximize business rule reuse and reduce design effort by implementing larger chunks of business logic across the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional manual identification of business rules is used, then design accuracy is maintained, but time consumption and design effort increase significantly
Solution Approach 1:
The patent replaces manual mechanical analysis of business rules with an automated computer-based system that uses pattern matching algorithms. The system automatically scans business logic, identifies patterns, and generates reuse opportunities without human intervention in the analysis process, thereby reducing time consumption while maintaining accuracy through systematic automated evaluation.
Solution Approach 2:
The system enables self-service by allowing the software development environment to automatically identify business rule reuse opportunities without requiring design engineers to manually analyze each rule. The automated pattern recognition system serves itself by continuously scanning and analyzing business logic, generating reuse candidates, and presenting them to engineers for review, thereby eliminating the time-consuming manual identification process.
2Manufacturing precision
If detailed business logic is captured at granular level, then implementation precision is improved, but complexity of identifying reusable rules increases
Solution Approach 1:
The patent segments the complex business logic into discrete, analyzable units by breaking down detailed business rules into smaller pattern elements. The system divides the granular business logic into identifiable pattern signatures that can be independently analyzed and matched, making the complex detailed logic manageable and reusable without losing implementation precision.
Solution Approach 2:
The system introduces an intermediary layer of pattern abstraction between the detailed business logic and the reuse identification process. This intermediary pattern-matching mechanism translates granular detailed logic into standardized pattern signatures, reducing the apparent complexity while preserving the precision needed for accurate reuse identification and implementation.
3Reliability
If comprehensive business rules are analyzed manually, then completeness of reuse identification is improved, but design effort increases
Solution Approach 1:
The patent replaces manual comprehensive analysis with automated computer-based scanning and pattern matching systems that can process all business rules systematically. The automated system maintains completeness by thoroughly analyzing every rule while significantly increasing design productivity through rapid automated processing compared to manual review methods.
Solution Approach 2:
The system enables continuous automated analysis of business rules without the interruptions and fatigue associated with manual review. The pattern recognition system continuously scans and analyzes business logic comprehensively, ensuring complete identification of reuse opportunities while maintaining high productivity through uninterrupted automated processing.
Data Source
AI summary
User interfaces and software reuse in model based software systems is disclosed. In one embodiment, user interface data is captured from business documents. Further, user interface elements are mapped to the business documents. A data model is formed for the business documents. A set of business rules for each business component in the data model is provided. A sequence of business rules associated with each action in the data model is scanned. In addition, a first pattern signature associated with an action that uniquely identifies each of the sequence of business rules is formed. It is determined if the first pattern signature is present in other actions in the data model. If so, the first pattern signature is included in a set of pattern signatures of the data model, else step of determining for a second pattern signature that is a subset of the first pattern signature is repeated.