Code Conversion Apparatus Automating Natural Language Generation
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Solution Overview
Problem
Current methods for code conversion require manual annotation and notation, making the process cumbersome and increasing the workload for programmers, as they need to manually add marks and notes for codes and construct flow charts of logical relationships, which is inefficient and prone to errors.
Innovation Solution
A method and apparatus for code conversion that reads and stores code lines into stacks, automatically converting them into natural language using a comparison table, eliminating the need for manual annotation and allowing intuitive display of logical relationships, with the ability to represent codes in different forms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual annotation and notation methods are used for code conversion, then code can be converted to natural language, but the workload of programmers significantly increases and the process becomes cumbersome
Solution Approach 1:
The system performs automatic code conversion without requiring programmer intervention. The conversion apparatus autonomously reads code files, analyzes syntax structures, matches phrases against the comparison table, and generates natural language descriptions, making the system self-sufficient and eliminating manual annotation work
Solution Approach 2:
The patent replaces the mechanical manual process of code annotation with an automated computational system. The conversion apparatus uses computer-based syntax analysis, phrase matching algorithms, and automatic text generation to substitute the manual mechanical process of programmers writing notes, thereby reducing workload while maintaining conversion capability
2Reliability
If manual notation and flow chart construction are required, then code logical relationships can be represented, but the process becomes inefficient and error-prone
Solution Approach 1:
The patent replaces error-prone manual flow chart construction with an automated computational system that programmatically analyzes code syntax structures, systematically extracts logical relationships, and accurately generates natural language descriptions, thereby improving both reliability and productivity simultaneously
Solution Approach 2:
The system incorporates a comparison table that stores predefined phrase mappings and logical relationship patterns. During conversion, the apparatus continuously references this table to verify phrase matches and ensure accurate logical relationship representation, providing a feedback mechanism that maintains high conversion accuracy
3Ease of operation
If codes are converted to natural language automatically, then programmer workload is reduced, but the system complexity increases due to syntax analysis and phrase matching mechanisms
Solution Approach 1:
The conversion apparatus divides the complex code conversion task into distinct modular components: a reading unit for input, a syntax analysis unit for structure parsing, a phrase matching unit for comparison table lookup, and a generation unit for output. This segmentation manages system complexity by organizing functions into separate, manageable modules
Solution Approach 2:
The patent introduces a comparison table as an intermediary data structure that stores predefined phrase mappings and logical relationship patterns. This intermediary layer simplifies the matching process by providing a standardized reference, reducing the complexity of direct code-to-natural-language translation while maintaining high conversion accuracy
Data Source
AI summary
The present invention relates to the field of computer programming, in particular, to a method and apparatus for code conversion in which the codes in the code file to be converted or the code tree to be converted is read and stored into the stack and popped up in the last-in first-out sequence of the stack, and then the code line or the child node currently popped up is resolved into the file to be converted, and lastly the natural semantics comparison table is traversed, and the inter-conversion between the codes and the natural language is automatically carried out, so as to avoid the programmers from manually adding the marks and notes for the codes, which greatly decreases workload of the programmers, and can intuitively display the direct logical relationship of the codes, and at the same time, depending on different situations, the codes can be represented selectively in different forms, facilitating the creating, searching and maintaining of the codes.