Optimization Tracing in Model Compilation Environments
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In modeling environments, users face difficulties in maintaining traceability between source and target representations of models due to optimizations performed during compilation, which can result in elements not having corresponding counterparts in the other representation, making it challenging to understand and manage the optimization process.
Innovation Solution
A computer-readable medium and method that provides instructions for obtaining, compiling, and displaying a listing of optimizations performed during the compilation process, allowing users to trace and visualize the optimization between source and target representations, including indicators that activate dynamic listings for both representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If optimization is performed during compilation to improve model efficiency, then compilation speed and model performance are improved, but traceability between source and target representations deteriorates
Solution Approach 1:
The patent introduces an intermediary mechanism (traceability infrastructure including mapping data structures and indicator systems) that mediates between the source representation and target representation. This intermediary layer preserves the relationship information even when optimizations transform the code structure, allowing users to trace back optimized code to its original source elements through the mapping infrastructure.
Solution Approach 2:
The system implements feedback by providing visual indicators in the target representation that show which portions correspond to source elements. This feedback mechanism allows users to verify traceability relationships and understand the impact of optimizations by seeing connections maintained between source and compiled code through the indicator system.
2Productivity
If optimization transforms code structure to improve performance, then model performance is improved, but understanding and managing the optimization process becomes difficult
Solution Approach 1:
The patent employs visual indicators (analogous to color changes or visual distinctions) in the target representation to highlight portions of code that result from optimizations. These indicators provide immediate visual feedback about which code segments have been optimized and their correspondence to source elements, making optimization management easier without sacrificing performance benefits.
Solution Approach 2:
The mapping infrastructure acts as an intermediary that bridges the gap between optimized code and source representation. This mediator provides users with tools to navigate, understand, and manage optimizations by showing relationships between transformed code and original source, thereby improving ease of operation while maintaining performance gains.
3Productivity
If elements are modified during compilation to achieve optimization, then compilation efficiency is improved, but corresponding counterparts in source and target representations become mismatched
Solution Approach 1:
The patent introduces a mapping data structure intermediary that maintains correspondence relationships between source elements and target elements even when optimizations cause structural changes. This intermediary records the relationships before and after transformations, allowing the system to maintain representation correspondence accuracy despite compilation efficiency optimizations that modify code structure.
Solution Approach 2:
The system performs preliminary action by establishing mapping relationships between source and target representations before optimizations are applied. This pre-established mapping infrastructure allows the compilation process to efficiently optimize code while the pre-recorded relationships ensure that correspondence information is preserved and can be retrieved later for traceability purposes.
Data Source
AI summary
A modeling environment is provided allowing a user to generate, from a source representation of a model, a target representation of a model and a listing of the optimization performed during generation of the target representation which is associated with the target representation or the source representation. The model may represent a system, such as a dynamic system. The source representation of the model may be a graphical or textual representation. In some embodiments a user may specify whether to implement the optimization.