Application Template Generation for Complex No-Code Inputs
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Solution Overview
Problem
Conventional no-code and low-code development platforms struggle to create templates for complex inputs such as business statements or audio files without manual human intervention, requiring specialized knowledge and leading to inefficiencies and coding errors.
Innovation Solution
A method and system that analyze an input request to extract keywords, generate a list of required services, and deploy an application using a template, allowing non-technical users to create and deploy software applications efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional NCDP and LCDP are used to analyze complex inputs such as business statements or audio files, then the system can recommend single APIs based on data features, but it cannot convert complex inputs into end-to-end software applications requiring multiple APIs
Solution Approach 1:
The system segments the complex template generation task into distinct components: an analysis component that processes input requests and extracts requirements, and a generation component that creates templates based on analyzed requirements. This segmentation allows the system to handle complex inputs by breaking down the overall task into manageable sub-tasks that can be processed independently and then integrated.
2Reliability
If manual human input and knowledge are required to create templates, then templates can be created with specialized knowledge, but non-technical users cannot create templates or deploy applications
Solution Approach 1:
The system introduces an intermediary automated template generation component that acts as a bridge between user requirements and technical template creation. This intermediary analyzes the input request, determines the necessary APIs and services, and generates the template automatically, eliminating the need for users to have specialized technical knowledge while ensuring template correctness through systematic analysis and generation processes.
3Productivity
If Large Language Models with additional training on IaC code are used, then template generation capability is improved, but issues with correctness and complexity of tasks remain
Solution Approach 1:
The system incorporates feedback mechanisms where the generated template is validated against the original input requirements and the actual deployment environment. The analysis component continuously refines its understanding based on deployment outcomes, and the generation component adjusts template creation based on feedback from validation results, ensuring both productivity and correctness are maintained through iterative improvement.
Data Source
AI summary
A computer-implemented method, program product, and systems for deploying an application in a software environment is provided. Embodiments of the present invention can analyze an input to extract at least one keyword and generate a list of at least one service for the input based on at least one keyword. Embodiments of the present invention can generate a template to satisfy the input request using the list of at least one service and deploy the application by applying the template.