Global Where-Used List for Layered Development Impact Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In a layered development environment for business software architecture, such as an ERP system, existing methods fail to accurately determine the impact of changes on development entities across multiple layers due to a lack of awareness of inter-layer dependencies, leading to manual effort-intensive impact analysis and potential cascades of errors.
Innovation Solution
A method is introduced that collects local dependency metadata from development systems, creates a global where-used list to aggregate intra-layer and inter-layer dependencies, and calculates a usage metric to quantify the impact of changes, providing a ranked list of affected entities and visualizations, along with notifications for developers and managers, using a high-performance in-memory database for real-time analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual impact analysis methods are used in a layered development environment, then developers can identify some dependencies, but the analysis is error-prone, time-consuming, and fails to capture inter-layer dependencies accurately
Solution Approach 1:
The patent introduces an intermediary system comprising a metadata repository and automated analysis engine that mediates between development entities across layers. This intermediary automatically collects, stores, and analyzes dependency metadata, eliminating the need for manual traceability while accurately capturing inter-layer dependencies that manual methods miss.
Solution Approach 2:
The patent replaces the mechanical manual process of impact analysis with an automated computational system. The automated analysis engine uses algorithms to process metadata, calculate impact metrics, and generate reports, substituting human effort with machine-based automation that is both faster and more accurate.
2Reliability
If comprehensive dependency tracking across all layers is implemented manually, then more dependencies can be identified, but the complexity and effort required becomes unmanageable
Solution Approach 1:
The patent implements self-service mechanisms where the system automatically generates and maintains its own dependency metadata. Development entities automatically report their dependencies to the metadata repository, and the system self-updates the global where-used lists without requiring manual intervention, thereby achieving comprehensive tracking with minimal operational complexity.
Solution Approach 2:
The patent segments the complex dependency tracking problem into manageable components: local where-used lists for individual development systems, a global metadata repository for centralized storage, and an automated analysis engine for processing. This segmentation allows each component to handle specific tasks independently, reducing overall system complexity while maintaining comprehensive tracking capability.
3Productivity
If automated impact analysis with global where-used lists is implemented, then analysis speed and accuracy improve, but the initial system setup and metadata collection infrastructure becomes more complex
Solution Approach 1:
The patent creates a universal metadata repository and automated analysis engine that serves multiple functions: storing dependency metadata, generating global where-used lists, performing impact analysis, and supporting multiple development systems across different layers. This multi-functionality consolidates what would otherwise require separate systems, reducing overall infrastructure complexity while enabling high-speed automated analysis.
Data Source
AI summary
Local dependency metadata can be collected from local metadata repositories of a plurality of development systems in a layered development system landscape, and a global where-used list that includes intra-layer and inter-layer dependencies between development entities in a layered development system landscape can be created, for example by aggregating the collected local dependency data. A usage metric quantifying how frequently each development entity is depended upon by other development entities in the layered development system landscape can be assigned to each development entity in the layered development system landscape. A measure of a relative effect of a change to one of the development entities on other development entities in the layered development system landscape can be promoted.