Augmented Program Analysis for Legacy Code Translation Compatibility
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Solution Overview
Problem
Existing technologies face challenges in translating computer code from obsolete programming languages like COBOL and PL/I to modern languages due to integration issues, scarcity of skilled programmers, slow development speed, and limited technical support, with current methods failing to handle large-scale applications and maintain compatibility.
Innovation Solution
Utilizing augmented program analysis metadata to construct target class structures and method prototypes, filter extraneous code, and employ a trained large language model to generate optimized translated code, ensuring compatibility and efficient memory handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If code translation is performed using traditional methods, then translation can be achieved, but translation speed is slow and scalability is limited
Solution Approach 1:
The patent segments the code translation process into distinct phases: metadata construction from original code, extraneous code filtering based on compatibility analysis, prompt generation using metadata-source code pairs, and optimization of generated code. This segmentation enables parallel processing and modular optimization, significantly improving translation speed while managing system complexity through structured organization of the translation pipeline.
Solution Approach 2:
The patent performs preliminary actions by constructing augmented program metadata and filtering extraneous code before the actual translation process. This pre-processing prepares the code in advance, allowing the main translation phase to operate more efficiently on pre-cleaned and structured data, thereby accelerating overall translation speed without proportionally increasing system complexity.
2Reliability
If all code from original programming language is translated, then completeness is maintained, but compatibility issues and redundancies increase
Solution Approach 1:
The patent extracts and removes extraneous code from the original codebase before translation based on determined code compatibility. This extraction process eliminates portions of code that would create compatibility issues or redundancies in the target language, ensuring that only essential and compatible code segments are translated. This maintains reliability by preventing known compatibility problems while simplifying the resulting code structure.
Solution Approach 2:
The patent applies local quality by treating different portions of the codebase differently based on their compatibility characteristics. Rather than uniformly translating all code, the system analyzes each segment's compatibility requirements and applies appropriate filtering and translation strategies locally, ensuring optimal compatibility for each code region while maintaining overall system integrity.
3Reliability
If translation maintains full functionality, then feature completeness is achieved, but memory handling efficiency decreases
Solution Approach 1:
The patent optimizes memory handling parameters in the generated code by analyzing and adjusting memory allocation patterns, data structure choices, and resource management strategies. This optimization maintains full functionality of the translated application while improving memory usage efficiency, reducing the energy and resources required for runtime operations in the target programming language.
4Stability of the object's composition
If archaic software systems are maintained using legacy languages, then system stability is preserved, but integration with modern systems becomes difficult
Solution Approach 1:
The patent acts as an intermediary system that bridges archaic software systems and modern computing environments. By translating legacy code from languages like COBOL and PL/I into modern languages while preserving original functionality, the system enables integration with contemporary systems and technologies without requiring modification of the original stable codebase, thus maintaining system stability while improving adaptability.
Solution Approach 2:
The patent creates accurate copies of legacy software functionality in modern programming languages. Rather than modifying the original archaic systems, the translation process generates equivalent functional copies in contemporary languages that can be integrated with modern systems, preserving the stability of original systems while achieving the adaptability needed for modern integration scenarios.
Data Source
AI summary
Systems and method for translating computer code using augmented program analysis. Augmented program metadata for a target computer code from an original code can be constructed by generating target class structure and target method prototype. Extraneous code can be filtered from the original code based on determined code compatibility to obtain filtered source code. A prompt can be generated using pairs of the augmented program metadata and the filtered source code that are fed to a trained large language model to obtain generated translated code. The generated translated code can be optimized to ensure code compilability, avoid redundancies, and enhance memory handling. A computer software application can be translated by compiling generated translated code.