Automated API Maturity Evaluation via Specification and Test Scoring
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Solution Overview
Problem
Manual verification of API design and code implementation is costly, difficult, and prone to inaccuracies, making it challenging to ensure the accuracy and stability of APIs, especially when comparing different APIs.
Innovation Solution
An automated API evaluation method that determines a specification score by comparing the API's definition description with a predetermined specification and a test score by applying a test case set to the API's code, with a maturity metric calculated based on these scores to assess the API's compliance and implementation quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual verification is used to evaluate API design and code implementation, then evaluation accuracy can be maintained through expert judgment, but the process becomes costly, time-consuming, and difficult to standardize
Solution Approach 1:
The patent replaces manual mechanical verification processes with automated computational systems. Specifically, it uses machine learning models to automatically evaluate API code quality, replacing expert human judgment with algorithmic assessment that can process multiple APIs simultaneously without additional time cost.
Solution Approach 2:
The patent creates standardized evaluation templates and checklists that can be copied and applied uniformly across different API evaluations. These standardized assessment frameworks enable consistent evaluation criteria to be replicated across numerous APIs, ensuring measurement precision while reducing the time required for each individual evaluation.
2Reliability
If manual verification is used to ensure API stability and accuracy, then quality control can be maintained, but the process becomes complex and difficult to scale
Solution Approach 1:
The patent transforms the verification process from a complex qualitative manual assessment into a standardized quantitative evaluation system. By defining specific parameters such as code completeness, specification compliance, and test coverage metrics, the system maintains reliability through measurable indicators while reducing process complexity through automated calculation.
Solution Approach 2:
The patent divides the API verification process into distinct modular components: code parsing, specification matching, test case execution, and quality scoring. Each component handles a specific aspect of verification independently, making the overall process less complex and easier to maintain while ensuring comprehensive reliability checks.
3Manufacturing precision
If comprehensive manual evaluation is performed on each API, then detailed quality assessment can be achieved, but the cost and difficulty increase significantly
Solution Approach 1:
The patent enables APIs to be automatically evaluated through self-service mechanisms where the system independently parses code, compares against specifications, executes test cases, and generates quality reports without requiring manual intervention. This maintains detailed quality assessment through comprehensive automated checks while dramatically improving evaluation ease.
4Measurement precision
If standardized evaluation metrics are implemented for API maturity assessment, then comparability between different APIs is improved, but the initial setup and standardization process becomes more complex
Solution Approach 1:
The patent develops a universal evaluation framework that can assess multiple types of APIs using the same standardized metrics and procedures. This multi-functional system handles different API languages, formats, and styles through a unified assessment approach, improving comparability while the initial standardization complexity is amortized across numerous evaluations.
Data Source
AI summary
A method, a device, and a program product for evaluating an application program interface (API) are provided in embodiments of the present disclosure. According to some embodiments, a method for evaluating an API includes determining a specification score of the API by comparing a definition description for the API with a predetermined specification corresponding to the API. The specification score indicates a degree of matching between the definition description and the predetermined specification. Additionally, the method for evaluating an API includes determining a test score for the API by applying a predetermined test case set to a code set of the API. The test score indicates a test status for the code set. Further, the method for evaluating an API includes determining a maturity metric of the API based on the specification score and the test score.