Metaprogramming Engine for Ontology-Based Backend Application Generation
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Solution Overview
Problem
Conventional backend application development is labor-intensive and costly, relying on human programmers and requiring manual processes, which limits scalability and increases the risk of errors and performance degradation.
Innovation Solution
A device and method using metaprogramming and domain ontology with syntactic and semantic formal specifications to generate backend applications, reducing dependency on human labor and automating quality assurance by applying a metaprogramming engine to ontology information, enabling efficient and error-free application generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If human programmers manually develop backend applications using entity relationship models and query languages, then the applications can be created with human judgment and flexibility, but the process becomes labor-intensive, costly, and difficult to scale
Solution Approach 1:
The patent replaces the mechanical system of manual programming with an automated ontology-based generation system. The metaprogramming engine automatically transforms domain ontologies into backend application code, eliminating the need for manual coding while maintaining application quality and functionality.
Solution Approach 2:
The system enables self-service application generation where the ontology model automatically serves as the specification for code generation. The metaprogramming engine uses the ontology structure and constraints to autonomously generate appropriate backend application code without requiring human programmers to manually translate requirements into code.
2Reliability
If manual processes are used for backend application development and quality assurance, then human reviewers can ensure quality and fix bugs, but the process becomes expensive and time-consuming
Solution Approach 1:
The patent performs quality assurance actions preliminarily during the code generation process itself. The metaprogramming engine embeds validation rules and constraints directly into the generation process, automatically checking for errors and ensuring quality standards are met before the application is deployed, eliminating the need for separate manual QA phases.
Solution Approach 2:
The system replaces manual quality review processes with automated validation mechanisms embedded in the metaprogramming engine. The engine automatically verifies that generated code meets specifications, constraints, and quality standards, providing reliable quality assurance without human intervention.
3Adaptability or versatility
If conventional manual development methods are used, then programmers can implement complex logic and handle edge cases, but the availability of qualified programmers is limited and costs increase
Solution Approach 1:
The patent creates a universal ontology-based development platform that can generate backend applications across multiple domains. The same metaprogramming engine and ontology framework can be applied to different business domains by simply changing the ontology model, providing versatility without requiring domain-specific programming expertise for each new application.
Solution Approach 2:
The ontology model serves as an intermediary between domain requirements and implementation code. It captures complex business logic, rules, and constraints in a structured format that the metaprogramming engine can automatically translate into appropriate code, handling complexity without requiring human programmers to directly implement each detail.
4Ease of operation
If traditional top-down high-level domain expert oriented techniques are used, then development is simplified, but performance degradation occurs
Solution Approach 1:
The patent replaces traditional high-level domain languages and manual optimization processes with an automated metaprogramming system that generates optimized code directly from ontologies. The engine produces efficient, performant code while maintaining the simplicity of ontology-based specifications, avoiding the performance degradation typically associated with high-level abstraction languages.
Data Source
AI summary
Embodiments of the innovation relate to, in a development device, a method of generating a backend application for execution by a server device. The method comprises receiving, by the development device, ontology information associated with an enterprise domain, the ontology information including syntactic information and semantic information; applying, by the development device, a metaprogramming engine to the ontology information to generate the backend application; and forwarding, by the development device, the backend application to the server device.