NLP Interpretation of Code Changes for Faster Issue Explanation
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Solution Overview
Problem
Existing systems struggle to accurately, efficiently, and dynamically determine natural language from computer programming language, making it difficult to fix and describe computer program issues to laypeople.
Innovation Solution
A system utilizing a trained NLP engine to identify change requests and modifications, generate natural language interpretations, and transmit them through a GUI, reducing resource usage and manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to translate computer programming language to natural language, then accuracy can be maintained through human review, but productivity is reduced due to time-consuming manual processes
Solution Approach 1:
The system enables computer programs to automatically generate and interpret their own code modifications through NLP engines, eliminating the need for manual human review while maintaining accuracy through automated natural language interpretation of code changes
Solution Approach 2:
The patent replaces manual mechanical translation processes with an automated NLP engine that uses machine learning algorithms to convert programming language modifications into natural language interpretations, significantly improving both speed and consistency
2Measurement precision
If comprehensive analysis of all code modifications is performed, then measurement precision of natural language interpretation is improved, but use of computing resources increases
Solution Approach 1:
The system extracts only the essential and relevant modifications from the computer program that need natural language interpretation, rather than analyzing every single code change. This selective extraction maintains interpretation accuracy while reducing unnecessary computing resource consumption on insignificant modifications
Solution Approach 2:
The NLP engine performs partial analysis by focusing on key modification areas that impact program functionality, rather than exhaustively analyzing every line of code. This approach achieves sufficient accuracy for practical purposes while conserving computing resources
3Adaptability or versatility
If dynamic determination of natural language is implemented, then adaptability to different programming scenarios is improved, but device complexity increases
Solution Approach 1:
The NLP engine is designed with multi-functionality to handle various programming languages and modification types through a unified architecture. It can dynamically adapt to different programming scenarios without requiring separate specialized systems, thereby improving versatility while managing complexity through a single versatile platform
Data Source
AI summary
Systems, computer program products, and methods are described herein for implementing natural language processing to determine natural language from computer programming language in an electronic environment. The present disclosure is configured to identify at least one change request associated with at least one computer program to: identify at least one modification to the at least one computer program; apply the at least one change request and the at least one modification to a natural language processor (NLP); generate a natural language interpretation of the at least one modification; generate a modification interpretation interface component, wherein the modification interpretation interface component comprises a data packet of the natural language interpretation; and transmit the modification interpretation interface component to a user device associated with the at least one change request and configure a graphical user interface (GUI) of the user device with the modification interpretation interface component.