Legacy Code Translation for Automated SysML Model Generation
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Solution Overview
Problem
Existing systems engineering processes for generating SysML models from legacy code are slow, costly, and reliant on skilled practitioners, limiting scalability and efficiency due to human intervention and limited availability of trained personnel.
Innovation Solution
A system and method utilizing a Large Language Model (LLM) to identify, translate, and generate text-based model assembly documents from code repositories, enabling automated generation of SysML architectural models without requiring extensive domain knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If skilled practitioners use GUI to manually create SysML models from legacy code, then model accuracy and domain knowledge requirements are satisfied, but development time and cost increase significantly
Solution Approach 1:
The patent introduces an intermediary system consisting of code analysis tools and natural language generation components that automatically translate legacy code into SysML model representations. This intermediary layer processes the code repository, extracts relevant information, and generates model assembly documents, eliminating the need for practitioners to manually analyze each component while preserving model accuracy.
Solution Approach 2:
The system enables the legacy codebase to essentially document itself by automatically generating SysML models from the existing code structure, comments, and documentation. The code repository serves its own documentation needs through automated analysis and model generation, reducing dependency on external expert intervention.
2Reliability
If skilled practitioners manually analyze and model complex legacy code repositories, then comprehensive system understanding is achieved, but resource availability and scalability are limited
Solution Approach 1:
The patent replaces the mechanical process of manual code analysis and model creation with an automated computational system. Instead of practitioners manually examining code and creating models through GUI interfaces, the system uses automated code parsing, analysis algorithms, and template-based model generation to achieve comprehensive system understanding at scale.
Solution Approach 2:
The system is designed to handle multiple types of code repositories, programming languages, and legacy systems through a universal framework. The code analysis component can process various code structures and formats, making the solution scalable across different projects and organizations without requiring specialized manual analysis for each case.
3Manufacturing precision
If extensive domain knowledge is required for manual SysML model creation, then model quality is maintained, but practitioner availability and training requirements increase
Solution Approach 1:
The system incorporates pre-configured knowledge bases, templates, and best practices embedded within the automated generation process. These preliminary resources contain domain knowledge and modeling standards that guide the automatic model creation, ensuring high model quality without requiring practitioners to possess extensive domain expertise.
Solution Approach 2:
The system uses templates and patterns that replicate proven modeling approaches and best practices. By copying established model structures and relationships from existing successful models, the system maintains high model quality standards while eliminating the need for practitioners to recreate these patterns manually with deep domain knowledge.
Data Source
AI summary
A framework for generating a systems engineering model for a legacy system includes identifying and extracting code from a specific legacy system or repository and/or codebase; translating the learned code by feeding it to a LLM that specializes in code understanding to elicit natural language descriptions of the functionality of each segment of code and generate a text based output useable by a SysML generator to generate a SysML model of the legacy system from the LLM output.