AI-Enhanced Model for Automated Code Generation
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Solution Overview
Problem
The development of software applications is hindered by the inefficiencies of manual code writing, lack of skilled programmers, and the challenges of maintaining and upgrading legacy software, which are costly, poorly documented, and prone to security vulnerabilities and compatibility issues with cloud environments.
Innovation Solution
The use of artificial intelligence tools to enhance and augment data models, allowing for the automatic generation of code and related artifacts, such as APIs and documentation, reducing the need for extensive manual coding and improving the comprehensibility of the generated code for non-programmers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual code writing is used, then software can be developed with existing tools, but development time and cost increase significantly
Solution Approach 1:
The patent replaces manual mechanical coding processes with AI-based automated code generation systems. The AI model analyzes data models and automatically generates corresponding software code, eliminating the need for manual programming while significantly improving development speed and reducing time loss.
Solution Approach 2:
The patent introduces an AI model as an intermediary between data models and final software code. This intermediary automatically translates data models into functional software artifacts, bridging the gap without requiring manual intervention and thereby increasing productivity while reducing development time.
2Reliability
If legacy software is maintained, then existing functionality is preserved, but security vulnerabilities and compatibility issues increase
Solution Approach 1:
The patent applies preliminary action by generating modern, secure software code from data models before legacy issues can manifest. By creating new software artifacts through AI-based code generation that inherently follows current security best practices and compatibility standards, the system prevents security vulnerabilities and compatibility problems before they occur, rather than maintaining outdated code.
Solution Approach 2:
The patent changes the fundamental parameter of code generation from manual/legacy-based to AI-driven/modern-based. This parameter change enables the generation of software that inherently incorporates current security standards and cloud compatibility, transforming the security and maintenance profile of the software lifecycle.
3Productivity
If AI tools are used to generate code, then development productivity improves, but code complexity and extension requirements increase
Solution Approach 1:
The patent implements feedback mechanisms where the AI model continuously refines code generation based on analysis of data models and requirements. This feedback loop ensures that generated code maintains appropriate complexity levels by automatically adapting to the specific needs of each application, preventing unnecessary complexity while preserving productivity benefits.
Solution Approach 2:
The patent applies dynamics by making the code generation process adaptive and flexible. The AI model dynamically adjusts code structure and complexity based on the specific data model and requirements, rather than applying fixed generation patterns. This dynamic approach generates code with optimal complexity for each case, maintaining high productivity without excessive complexity.
Data Source
AI summary
A method or system uses AI-based enhancement to improve an initial model, such as an abstract model of a database, before the abstract model is submitted to an automated code author. The AI, which may be a generative AI, can assist with identifying parts of the abstract model (such as UML artifacts) and suggest revisions, according to a series of interactions between a developer and AI. The result of this interaction with the AI is then used to revise or augment the abstract model. Ultimately, the AI-enhanced model is consumed by a code author to generate application source code.