Cloud API Recommendation Engine for Automated Quality Assessment
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Solution Overview
Problem
Developers face difficulty in selecting the appropriate web API from thousands of available options due to the complexity of determining the quality and performance of each API, especially when integrating automated test processes.
Innovation Solution
A cloud computing service retrieves test source code, identifies calls to specific web APIs, extracts usage information from log files, and recommends higher-quality APIs based on aggregated quality metrics, providing real-time recommendations to developers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If developers manually evaluate each web API from thousands of options, then they can select the most suitable API, but the time and effort required increases significantly
Solution Approach 1:
The system enables self-service by automatically evaluating APIs through log file analysis and quality metric computation, allowing the system to serve itself in identifying suitable APIs without manual developer intervention for each evaluation
Solution Approach 2:
The system implements feedback mechanisms by analyzing runtime log data from actual API usage, continuously improving quality assessments based on real-world performance data and feeding this information back to developers through automated recommendations
2Measurement precision
If developers analyze comprehensive quality metrics for each API, then selection accuracy improves, but the complexity of the evaluation process increases
Solution Approach 1:
The system extracts only the essential quality metrics from comprehensive log data that are most relevant to API evaluation, separating critical performance indicators from unnecessary detailed information to maintain measurement precision while reducing complexity
Solution Approach 2:
The evaluation system is designed to be universal by handling multiple API types and formats through a standardized quality assessment framework, enabling the same system to evaluate diverse APIs without requiring separate complex evaluation processes for each
3Reliability
If the system analyzes log files from multiple applications, then the quality assessment becomes more reliable, but the data processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-processing and indexing log data as it is generated, organizing information in advance to enable faster aggregation and analysis when quality assessments are requested, reducing the processing time for comprehensive multi-application analysis
Data Source
AI summary
A method for recommending a web application programming interface (API) includes: a cloud computing service retrieving test source code from a remote computer of the developer; the cloud computing service determining whether a call to a first web API among a plurality of web APIs is present in the test source code; and when it is determined that the call is present, the cloud computing service reading at least one log file to extract information about at least one application that has used the first web API; the cloud computing service determining a first quality of the first web API from the log file; and the cloud computing service sending a message to the remote computer recommending a second web API among the web APIs having a second quality higher than the first quality.