Software Code Syntax Comparison and Analysis System
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Solution Overview
Problem
Programming systems face challenges in improving the compatibility, usability, and security of software programs by efficiently modifying and incorporating existing code, as existing methods lack effective syntax comparison and analysis tools to identify and integrate suitable code modules.
Innovation Solution
A system and method that compares the syntax and attributes of an input software program with databased programs to generate improvements, involving language identification, compilation, syntax analysis, similarity rating, and code module generation, using machine learning-based AI to suggest modifications and optimize code.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If syntax comparison and analysis tools are implemented to identify and integrate suitable code modules, then compatibility and security of software programs are improved, but system complexity and computational resources required increase
Solution Approach 1:
The system divides the code analysis process into distinct modular components: syntax analysis module, semantic analysis module, similarity comparison module, and code integration module. Each module handles a specific aspect of code comparison, making the overall complex system manageable and maintainable while achieving comprehensive code compatibility and security verification
Solution Approach 2:
The patent introduces an intermediary AI/ML-based code analysis system that acts as a mediator between existing code modules and the integration process. This intermediary automatically performs syntax comparison, semantic analysis, and compatibility verification, reducing the need for complex manual analysis tools while improving reliability
2Reliability
If comprehensive syntax analysis and similarity comparison are performed on code modules, then code compatibility and functionality are improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary syntax analysis and categorization of code modules before actual integration. By pre-processing and indexing code structures, the system prepares data in advance, enabling faster comparison and compatibility verification during the actual code integration process
Solution Approach 2:
The patent employs AI/ML models that adapt analysis depth and parameters based on code characteristics. For simple code modules, the system performs lightweight syntax checking, while for complex modules, more comprehensive analysis is applied. This dynamic parameter adjustment reduces overall processing time while maintaining compatibility reliability
3Reliability
If AI-based code analysis and optimization are implemented, then code quality and security are improved, but ease of operation and implementation difficulty increase
Solution Approach 1:
The system implements self-service capabilities where the AI-based code analysis tool automatically performs syntax comparison, security verification, and compatibility checking without requiring manual configuration. The system self-adapts to different programming languages and code structures, making it easy to operate while maintaining high code quality and security standards
Data Source
AI summary
Aspects of the subject disclosure may include, for example, a method in which a processing system loads a software program into compilers associated with different programming languages to identify a language of the software program, determines whether the software program is executable in the identified language, and compiles the software program to generate executable code. The system retrieves executable programs in the identified language from a program database, analyzes a syntax of the executable code and the executable programs, compares attributes of the executable code and the executable programs, and determines similarity ratings for the executable programs with respect to the executable code. The system also generates a code module comprising the executable code and at least a portion of the executable programs, based at least in part on the similarity ratings. Other embodiments are disclosed.