Metadata Orchestrator Automates Application Code Generation
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Solution Overview
Problem
In organizations, internal systems development efforts are often dispersed and fragmented, leading to repetitive, time-consuming tasks in application development, with limited reusability and control of efforts across different applications.
Innovation Solution
A system that employs a metadata library and orchestrator to centralize control, generate source code automatically, produce documentation, and deploy it to a hosting environment, leveraging adaptors to automate tasks such as data store interactions without human intervention, thereby enhancing reusability and reducing manual mapping efforts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If application development efforts are dispersed and fragmented across different projects, then each application can be developed independently with its own configurations, but repetitive manual mapping tasks must be performed in each development effort, consuming considerable time and effort
Solution Approach 1:
The patent merges scattered development efforts into a centralized metadata-driven platform. By combining multiple application configurations into a unified metadata library, the system eliminates repetitive manual mapping tasks while maintaining independent application development capabilities through automated code generation from shared metadata definitions.
Solution Approach 2:
The patent creates a universal metadata library that serves multiple application development efforts simultaneously. This metadata-driven approach enables a single set of definitions to be reused across different applications, providing multi-functionality that reduces repetitive work while supporting diverse application needs through automated adaptation.
2Reliability
If special machines and systems are created for various tasks and applications, then each system can be entirely functional on its own, but reusability and leverage of those efforts at organizational levels is limited
Solution Approach 1:
The patent uses metadata as a reusable template that can be copied and applied across multiple applications. By defining configurations once in the metadata library and automatically generating code from these templates, the system enables organizational-level reusability while maintaining functional independence of each application through automated instantiation.
Solution Approach 2:
The patent performs preliminary action by pre-defining metadata configurations and relationships in a centralized library before actual application development begins. This advance preparation enables rapid, consistent deployment across multiple applications without requiring repetitive manual work, thereby improving both reusability and functional reliability.
3Ease of operation
If manual mapping tasks are performed for each application configuration, then detailed control over data store interactions can be achieved, but development time increases significantly with hundreds of hours spent on mundane tasks
Solution Approach 1:
The patent implements self-service by enabling automated code generation from metadata definitions. The system automatically performs mapping tasks, generates data access code, and configures interactions without manual intervention, thereby maintaining detailed control over data store interactions while dramatically improving development productivity through elimination of repetitive manual work.
Solution Approach 2:
The patent replaces manual mechanical mapping tasks with an automated metadata-driven system. By substituting human-performed mapping operations with automated code generation based on metadata templates, the system maintains precise control over data interactions while eliminating the time-consuming manual effort, thereby resolving the contradiction between control and productivity.
Data Source
AI summary
Building and deployment of multiple applications can be augmented using metadata. Source code of a service can be generated automatically in a programming language without human intervention based on metadata descriptive of a data store and desired interaction with the data store by the service. Furthermore, documentation can be created automatically based on the metadata, wherein the documentation comprises at least one of application programming interface (API) data, data definitions, or end-user help document.