Natural Language Program Generation via Intent Validation
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Solution Overview
Problem
Current techniques for creating computer programs do not utilize natural language processing technology, requiring manual coding or drag-and-drop methods that lack efficiency and expertise.
Innovation Solution
A system and method that utilize natural language input processed by a machine learning model to predict intent, validate, and automatically convert it into executable computer commands, generating a computer program.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual coding or drag-and-drop tools are used to create computer programs, then program creation is possible, but the process requires significant expertise and time
Solution Approach 1:
The patent replaces manual coding mechanics with natural language processing. Instead of requiring users to manually write code or drag-and-drop components, the system processes natural language input through NLP pipelines, intent recognition models, and automated code generation algorithms to produce functional programs, thereby substituting mechanical programming operations with intelligent language processing
Solution Approach 2:
The system enables self-service program creation by automatically generating code from natural language descriptions without requiring user expertise in programming languages or software development methodologies. The automated intent recognition and code synthesis mechanisms allow the system to serve itself in translating user requirements into executable programs
2Adaptability or versatility
If natural language processing technology is not utilized in program creation, then existing manual methods can be used, but the technology available for other tasks remains underutilized
Solution Approach 1:
The patent applies natural language processing technology universally across multiple stages of program creation: input processing, intent recognition, parameter extraction, code generation, and validation. The same NLP infrastructure that powers other AI tasks is leveraged to perform diverse functions in the software development lifecycle, demonstrating multi-functionality and versatility of the technology
Solution Approach 2:
The system introduces natural language as an intermediary between user requirements and program code. Instead of direct manipulation of code or graphical interfaces, users communicate their needs through natural language, which serves as a mediator that the NLP system translates into structured intent representations and subsequently into executable programs, simplifying the interaction model
3Ease of operation
If manual coding methods are used, then program creation is achievable, but expertise in programming languages is required
Solution Approach 1:
The patent substitutes mechanical programming operations with natural language processing. Instead of requiring users to learn and apply programming syntax, semantics, and software engineering principles, the system processes natural language input through NLP pipelines, intent recognition models, and automated code generation algorithms to produce functional programs, thereby making program creation accessible to non-experts
Data Source
AI summary
As described herein, a system, method, and computer program are provided for creating a computer program from natural language input. Input is received from a natural language processor. The input is processed, using a machine learning model, to predict an intent of the input. A validation of the intent is performed. The intent is automatically converted to one or more executable computer commands, based on a result of the validation of the intent. The one or more executable computer commands are executed to generate a computer program.