Software Code Migration Using Dynamic Knowledge Engine
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Solution Overview
Problem
Existing technologies are limited in discovering, recognizing, and extracting knowledge elements from diverse systems, are non-flexible, produce proprietary outputs, and lack adaptability due to fixed rules, inability to achieve an abstract view of input data, and inability to dynamically interpret and convert software code effectively.
Innovation Solution
An apparatus that uses a knowledge engine coupled with a custom knowledge base to analyze and convert source code from any platform to any target platform, utilizing ASCII input, UI/GUI details, and fuzzy rules to create workflow diagrams and generate target architecture, allowing for iterative updates and manual conversion of unconverted code.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fixed static rules are used for code transformation, then the transformation process is simple and fast, but the system cannot adapt to diverse systems and produces proprietary outputs
Solution Approach 1:
The patent applies dynamics by transforming the fixed static rules into dynamic patterns that can be modified at runtime. The pattern recognition system dynamically adapts to different source systems by learning their specific characteristics during the transformation process, allowing the same system to handle diverse codebases without reconfiguration.
Solution Approach 2:
The system performs self-service by automatically learning and adapting to the characteristics of source systems through pattern recognition. It self-adjusts its transformation rules based on the input code patterns it encounters, eliminating the need for manual configuration for each new system type.
2Productivity
If simple transformation and syntax matching techniques are used, then the processing is fast and resource-efficient, but the system cannot achieve an abstract view of input data and performs only line-by-line transformation
Solution Approach 1:
The patent applies another dimension by transitioning from line-by-line syntax matching to a multi-dimensional abstract view of code. It analyzes code at multiple levels including semantic meaning, control flow, and data flow, enabling accurate understanding while maintaining processing efficiency through hierarchical analysis.
Solution Approach 2:
The system replaces mechanical syntax matching with intelligent pattern recognition algorithms. Instead of rigid character-by-character comparison, it uses learned patterns to understand code semantics, allowing accurate code transformation while maintaining processing speed through efficient pattern matching.
3Device complexity
If pattern recognition is static and pre-defined, then the system is simple to implement, but it cannot perform self-interpretation or dynamically hatch new patterns
Solution Approach 1:
The system applies preliminary action by pre-defining a base set of transformation patterns that cover common code structures. These preliminary patterns provide a foundation that can be quickly applied to standard cases while allowing the system to learn and add new patterns for specialized scenarios.
Solution Approach 2:
The patent implements feedback by using the results of pattern recognition to continuously refine and expand the pattern library. When the system encounters new code patterns during transformation, it learns from these experiences and updates its pattern recognition capabilities for future use.
Data Source
AI summary
An apparatus migrates and/or converts any source application working on any platform into a format of any target platform. It comprises an inputting means for accepting the entire source code of sample part in ASCII to analyze the business logic of the source application and corresponding data; an analyzing means for analyzing the source schemes; a setting up means for generating (updating or creating) custom knowledge base; a processing means for conversion of source code in format of target specification; and A documenting means for generation of reports during review of the process stage and a summary report after the end of the conversion process, which consists of the code that is not converted automatically.