Generative AI Code Updating for Data Source Compliance

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Solution Overview

Problem

Existing software applications face challenges in efficiently and accurately updating their code to comply with changes in data sources, such as tax laws or regulations, due to the complexity and length of the task, which often requires significant manual labor and is prone to human error.

Innovation Solution

A method utilizing embeddings and machine learning models to compare versions of a data source and generate updated software application code, involving a data source comparison engine and a code update engine with trained machine learning models to ensure semantic and syntactic correctness.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual updating of software code is performed to comply with data source changes, then the software can be updated with human judgment and error correction, but the process requires immense manual labor and is prone to human error

Engineering Contradiction:

Improveaccuracy of code updatesVSAvoidtime required for code updates

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs automated code updates by having the software application itself generate update code in response to detected data source changes, eliminating the need for extensive manual intervention while maintaining accuracy through automated verification processes

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical coding processes with an automated system that uses machine learning models and natural language processing to generate, review, and apply code updates automatically

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If automated diff operation is performed to compare data source versions, then the comparison is fast and objective, but it provides no insight into how differences relate to existing software code or how to update the code

Engineering Contradiction:

Improvespeed of data source comparisonVSAvoidcontextual information for code updates

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The system introduces an intermediary natural language description layer between the automated diff operation and the code update process. This intermediary translates technical differences into contextualized instructions that bridge the gap between raw comparison data and actionable code changes

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces purely mechanical diff operations with an intelligent system that uses natural language processing and machine learning to interpret differences and generate contextualized update instructions

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Manufacturing precision

If extensive manual code updating is performed, then comprehensive review and verification can be conducted, but the complexity and length of the task increase the chance for human error

Engineering Contradiction:

Improveprecision of code updatesVSAvoidcomplexity of update process

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The system segments the complex code update process into distinct automated stages: detection of data source changes, generation of natural language descriptions, creation of update code, and verification. Each segment handles a specific aspect, reducing overall process complexity while maintaining precision

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system implements automated feedback loops where generated code updates are verified against the data source changes, and corrections are automatically applied. This feedback mechanism ensures precision without requiring manual review of every line of code

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12430123B2Generative AI system for automated programming and accelerated code modification

Publication Date: 2025.09.30 INTUIT INC

AI summary

Aspects of the present disclosure relate to automatically updating a software application to ensure compliance with an updated data source. Embodiments include providing an embedding of a first version of a data source and an embedding of a second version of the data source to a comparison engine configured to compare the embedding of the first version of the data source and the embedding of the second version of the data source and generate a data source difference summary. Embodiments further include providing an embedding of a software application code module and the data source difference summary to a code update engine trained to generate an updated version of the software application code module based on the embedding of the software application code module and the data source difference summary. Embodiments further include updating code of the software application using the updated version of the software application code module.