API Interface Semantic Marking for Functional Identification
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Solution Overview
Problem
Current API interfaces lack clear functional and name information, complicating maintenance, increasing operational and security protection costs, and reducing efficiency.
Innovation Solution
A method and apparatus that utilize a target model to semantically analyze API interface information, extracting functional description and name information, and mark the API interfaces for easier management and identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If API interface information is not marked with functional description and name information, then the system maintains simplicity and avoids additional processing complexity, but the maintenance difficulty increases and operational efficiency decreases
Solution Approach 1:
The patent applies preliminary action by pre-training the target model with API interface information, functional descriptions, and name information before actual use. This preprocessing step enables the model to automatically extract and mark API interface characteristics during operation, resolving the contradiction by preparing the system in advance rather than processing complexity during runtime.
Solution Approach 2:
The patent introduces a target model as an intermediary between raw API interface information and the final marked output. This intermediary component automatically extracts functional descriptions and name information, eliminating the need for manual marking while maintaining system simplicity. The model acts as a mediator that transforms unstructured data into organized, manageable information.
2Measurement precision
If manual marking of API interfaces is performed, then accurate functional description information can be obtained, but the time consumption and operational costs increase significantly
Solution Approach 1:
The patent implements self-service by enabling the target model to automatically extract and mark API interface functional descriptions and names without human intervention. The model processes API interface information autonomously, eliminating manual marking operations while maintaining high accuracy through its trained capabilities.
Solution Approach 2:
The patent replaces the mechanical manual marking process with an automated machine learning model. Instead of human operators manually analyzing and marking API interfaces, the target model performs this task automatically, substituting human cognitive work with computational processing that achieves comparable or superior accuracy while dramatically reducing time consumption.
3Measurement precision
If comprehensive API interface information is collected and analyzed, then marking accuracy improves, but the processing complexity and computational resources increase
Solution Approach 1:
The patent applies extraction by having the target model selectively extract only the necessary functional description and name information from comprehensive API interface data. Rather than processing all available information equally, the model identifies and extracts relevant features, reducing processing complexity while maintaining marking accuracy through focused analysis of key parameters.
Data Source
AI summary
The present disclosure provides a method, apparatus, electronic device, storage medium and product of marking an API interface. The method comprises: obtaining API interface information in API interface access traffic data; inputting the API interface information into a target model to obtain first information about the API interface information output by the target model; wherein the first information comprises at least one of: functional description information and interface name information of the API interface, and wherein the target model is trained based on first training data, and the first training data comprises first interface information and at least one of corresponding first functional description information or first interface name information; and marking the API interface based on the first information.