LLM Legacy Code Translation With Output Reconciliation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Legacy programming languages like COBOL and Sybase are difficult to integrate with modern technologies, and finding skilled developers for Perl-based systems is challenging, hindering the implementation of modern features and security measures in financial systems.
Innovation Solution
Utilizing a Large Language Model (LLM) to convert legacy code from COBOL, Sybase, or Perl to a human-readable description, which is then validated and translated to a modern programming language like Java or Python, with the LLM also generating test scripts and reconciling outputs to ensure compatibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If legacy code in COBOL, Sybase, or Perl is used to maintain existing financial systems, then system stability and existing functionality are preserved, but integration with modern technologies and implementation of new features become difficult
Solution Approach 1:
The patent uses an intermediary translation system that converts legacy code into modern programming languages. The system acts as a mediator between old and new technologies, allowing financial institutions to adopt modern languages (Java, Python, C#) while preserving the functional integrity of legacy systems through automated translation and validation processes.
Solution Approach 2:
The patent applies preliminary validation and testing mechanisms before full deployment of translated code. The system performs static analysis, dynamic testing, and validation against business rules prior to replacing legacy code, ensuring that modernized code maintains system stability while gaining adaptability.
2Adaptability or versatility
If manual code conversion from legacy languages to modern languages is performed, then code modernization is achieved, but conversion time and cost increase significantly
Solution Approach 1:
The patent replaces manual mechanical code conversion with an automated intelligent system. The system uses advanced algorithms to analyze legacy code structure, semantics, and business logic, then automatically generates equivalent code in modern languages, eliminating the time-consuming manual translation process while maintaining conversion accuracy.
Solution Approach 2:
The patent creates accurate copies of legacy code functionality in modern languages through automated translation. The system preserves the original business logic and operational behavior while rewriting code in contemporary programming languages, enabling rapid modernization without losing functional fidelity.
3Manufacturing precision
If comprehensive validation and testing of converted code is performed, then output accuracy and functionality are ensured, but processing time and computational resources increase
Solution Approach 1:
The patent implements a multi-level validation approach where critical paths and business rules receive exhaustive testing, while less critical areas undergo streamlined validation. The system performs targeted static analysis on high-risk code segments and uses intelligent sampling for other areas, achieving high accuracy without proportionally increasing processing time across the entire codebase.
Data Source
AI summary
Computer-implemented systems and methods use a Large Language Model (LLM) for converting a legacy computer program in a first language to a human-language description of the legacy computer program, which description can be validated as being an accurate description of the legacy computer program. Once validated, the human-language description can be converted, again using an LLM, to a computer program in a target programming language. An LLM can also be used to generate test scripts for the new target-language program to test the performance of the target-language program in a production environment. An LLM can also be used to reconcile outputs from the legacy program to the new target program, such as on a function-by-function basis. If the differences between the outputs (if any) are sufficiently negligible, the legacy computer program can be decommissioned, and the new, target language program can be used in production.