Automated Graph API Conversion from Operation-Centric Interfaces
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Solution Overview
Problem
Developers face challenges in integrating and managing multiple operation-centric APIs across diverse systems in ERP landscapes, requiring manual coding and inefficient processes for conversion to graph-based APIs.
Innovation Solution
A host system performs a two-step process to convert operation-centric APIs into graph-based APIs, involving operation identification, clustering, and entity relationship analysis, with the option for manual fine-tuning through a user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual coding is used to convert operation-centric APIs to graph-based APIs, then conversion accuracy can be maintained, but development time and costs increase significantly
Solution Approach 1:
The system enables automatic self-service conversion of APIs by using heuristic programs to autonomously analyze operation-centric APIs, identify entities and relationships, and generate graph-based API code without requiring manual developer intervention for each conversion task
Solution Approach 2:
The patent replaces the mechanical manual coding process with an automated computational system that uses heuristic analysis and algorithmic generation to transform APIs, substituting human developer labor with machine-based automation while maintaining conversion quality
2Manufacturing precision
If manual conversion process is used, then code quality can be controlled, but productivity decreases
Solution Approach 1:
The automated system performs self-service conversion with built-in quality control mechanisms, including heuristic validation and optional developer review stages, enabling high-volume conversions while maintaining code quality standards through systematic rather than manual processes
Solution Approach 2:
The system transforms the conversion process from a manual parameter-controlled process to an automated one where parameters such as heuristic rules, conversion templates, and quality thresholds can be adjusted to balance code quality and conversion throughput based on specific requirements
3Measurement precision
If developers manually identify and use correct APIs across diverse systems, then integration accuracy improves, but the complexity of the process increases
Solution Approach 1:
The system provides a universal automated conversion framework that handles diverse operation-centric APIs across different systems and protocols through a single multi-functional platform, eliminating the need for developers to manually navigate diverse API landscapes while maintaining integration accuracy
Data Source
AI summary
Provided are systems and methods for transforming an operation-centric API into a graph-based API. In one example, a method may include receiving a description of an application programming interface (API), translating the description into a proxy model that comprises a list of a plurality of operations performed by the API, executing one or more heuristic programs on the proxy model to determine a plurality of entities associated with the list of operations and relationships among the plurality of entities, generating a graph API based on the plurality of entities and the relationships among the plurality of entities, wherein the graph API comprises a plurality of nodes representing the plurality of entities and edges between the plurality of nodes representing the relationships between the plurality of entities, and storing the graph API in a storage.