Model Annotation System for MDA Precision and Productivity
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Solution Overview
Problem
In model-driven engineering, managing and modifying large numbers of software applications with numerous models and elements is impractical due to the difficulty in applying desired profiles consistently and efficiently, leading to incomplete or incorrect annotations.
Innovation Solution
A system comprising a query interpreter, profile reader, and profile integrator that queries a model repository, reads profile meta-models, and annotates elements with annotations to create an annotated model, allowing for flexible and automatic annotation of models, even with large numbers of models and profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual annotation of model elements is performed, then annotation precision can be ensured, but productivity decreases due to the large number of models and elements
Solution Approach 1:
The system enables automatic annotation of model elements by querying the model repository and applying profile annotations without requiring manual intervention for each element. The annotation engine automatically retrieves models, applies appropriate profiles, and generates annotated models, allowing the system to serve itself in the annotation process.
Solution Approach 2:
An annotation engine is introduced as an intermediary component between the model repository and the annotation profiles. This mediator automatically manages the annotation process by querying models, selecting appropriate profiles, and applying annotations, thereby resolving the contradiction between precision and productivity.
2Reliability
If consistent annotation of all model elements is attempted, then reliability of model annotations improves, but device complexity increases due to managing large numbers of models and profiles
Solution Approach 1:
The system segments the annotation process into distinct functional components: a query interpreter for retrieving models, a profile reader for managing annotations, and an annotation engine for applying profiles. This segmentation allows each component to handle specific tasks independently, maintaining reliability while managing complexity through modular organization.
Solution Approach 2:
The annotation engine serves multiple functions: querying the model repository, reading profile definitions, selecting appropriate profiles for model elements, and applying annotations. This multi-functionality reduces the need for separate specialized tools, maintaining consistent annotation across diverse model elements while managing system complexity.
3Productivity
If automatic annotation is implemented to improve productivity, then annotation speed increases, but manufacturing precision decreases due to potential incorrect annotations
Solution Approach 1:
The system implements feedback mechanisms where the annotation engine queries the model repository to understand model structures and relationships, selects profiles based on this information, and applies annotations. The system can detect and correct annotation errors by validating against model constraints and profile definitions, ensuring accuracy while maintaining high productivity through automation.
Data Source
AI summary
A query interpreter may be configured to query a model repository to obtain one or more elements of at least one model associated with a software application and stored in the model repository. A profile reader may be configured to read, from a profile repository, at least one profile meta-model that is associated with at least one annotation; and a profile integrator may be configured to annotate the one or more elements with the at least one annotation to obtain an annotated model.