Automated OData API Performance Testing Framework
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Solution Overview
Problem
Current API hubs lack a mechanism for efficiently testing the performance of OData APIs, making it cumbersome for users to determine if underlying operations are performing optimally, especially since existing methods do not allow for iterative testing and provide no performance details.
Innovation Solution
An automated performance testing framework is introduced, allowing end-to-end testing of OData APIs through a user-friendly interface, which enables users to select APIs, specify iteration numbers, and record average response times, facilitating efficient evaluation and optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual asynchronous execution is used to test APIs, then users can execute selected APIs, but it is cumbersome to collate results and no performance details are provided
Solution Approach 1:
The system pre-configures performance testing parameters, iteration counts, and result collection mechanisms before the actual API testing begins. This preliminary setup automates the entire testing workflow, eliminating the need for manual execution and result collation, thereby reducing debugging and optimization time while maintaining ease of operation.
Solution Approach 2:
An automated testing framework acts as an intermediary between the user and the API testing process. This framework automatically executes API calls, collects responses, collates results, and presents performance metrics, freeing users from manual testing tasks and providing comprehensive performance details that were previously unavailable.
2Measurement precision
If a single GET request is made to an OData API, then a response is provided, but the operation cannot be iterated more than once and no performance details are available
Solution Approach 1:
The system implements periodic repetition of API calls with configurable iteration counts. Instead of a single GET request, the framework automatically executes the same API call multiple times according to user-defined parameters, enabling performance measurement across multiple iterations while maintaining the simplicity of the original GET request operation.
Solution Approach 2:
The automated testing framework ensures continuous execution of API calls without interruption, automatically collecting performance metrics across all iterations. This continuous action provides comprehensive performance data including average response times, while maintaining the versatility to test any OData API endpoint that originally supported single GET requests.
3Productivity
If no automated testing mechanism is provided, then users have full control over API testing, but they cannot efficiently determine whether underlying OData operations are performing optimally
Solution Approach 1:
The automated testing framework performs self-service by automatically executing API tests, collecting performance metrics, analyzing results, and presenting optimization recommendations without requiring complex user configuration or manual intervention. This self-service capability dramatically improves performance evaluation efficiency while the framework's automated nature keeps the effective complexity low for users.
Data Source
AI summary
A method includes retrieving application programming interface (API) information including API calls from a plurality of APIs stored in a database, receiving, via a graphical user interface, a selection of one or more of the API calls retrieved from the database, receiving, via the graphical user interface, an input specifying a number of iterations to perform each of the selected one or more API calls, executing the selected one or more API calls on a target computer system for the specified number of iterations, retrieving performance information from the target computer system, and displaying the performance information on the graphical user interface.