27 Software U.S. Inc. dba DXterity Solutions (20240378029). AUTOMATED AUTHORING OF SOFTWARE SOLUTIONS FROM AN AI-ENHANCED MODEL simplified abstract
Contents
AUTOMATED AUTHORING OF SOFTWARE SOLUTIONS FROM AN AI-ENHANCED MODEL
Organization Name
27 Software U.S. Inc. dba DXterity Solutions
Inventor(s)
Christopher Zee Chartrand of Brantford (CA)
AUTOMATED AUTHORING OF SOFTWARE SOLUTIONS FROM AN AI-ENHANCED MODEL - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240378029 titled 'AUTOMATED AUTHORING OF SOFTWARE SOLUTIONS FROM AN AI-ENHANCED MODEL
Simplified Explanation:
The patent application describes a method or system that utilizes AI-based enhancement to improve an initial model, such as an abstract model of a database, before it is submitted to an automated code author. The AI, which could be a generative AI, assists in identifying parts of the abstract model and suggests revisions through interactions with a developer. The revised abstract model is then used by the code author to generate application source code.
- AI-based enhancement to improve initial models
- Utilization of generative AI to identify and suggest revisions to abstract models
- Interactions between developer and AI to enhance the abstract model
- Use of the AI-enhanced model by a code author to generate application source code
Key Features and Innovation:
- AI-based enhancement for abstract models
- Generative AI assistance in identifying and revising model parts
- Interactive process between developer and AI
- Improved abstract model for code generation
Potential Applications:
- Software development
- Database modeling
- AI-assisted coding
Problems Solved:
- Enhancing abstract models efficiently
- Improving code generation process
- Streamlining software development
Benefits:
- Faster development cycle
- Higher quality code
- Enhanced productivity for developers
Commercial Applications:
The technology can be applied in various industries such as software development, database management, and AI-driven applications. It can streamline the development process, improve code quality, and increase productivity for developers.
Questions about AI:
1. How does the AI-based enhancement process improve the efficiency of abstract model development?
The AI assists in identifying and revising parts of the abstract model, leading to a more refined and accurate representation before code generation.
2. What are the potential long-term implications of using generative AI in software development processes?
The use of generative AI can lead to more efficient and accurate code generation, ultimately improving the overall quality and speed of software development projects.
Original Abstract Submitted
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.
