Scriptless Test Automation via Dynamic Selector Selection
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Solution Overview
Problem
Traditional test automation for web pages requires manual selection of identification mechanisms and steps, which is skill-intensive and prone to obsolescence due to rapid changes in user interface and user experience, necessitating frequent updates.
Innovation Solution
A computer-implemented method and system that stores test steps as metadata objects with unique identifiers, allowing an interpreter algorithm to dynamically choose the best identification mechanism and generate necessary commands, decoupling test automation from specific UI/UX changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual selection of identification mechanisms and steps is used, then test automation can be performed, but it requires skill-intensive manual intervention and is prone to obsolescence
Solution Approach 1:
The system performs self-service by automatically selecting identification mechanisms and generating test commands without requiring manual intervention. The interpreter algorithm analyzes metadata and autonomously determines the best selector and interaction steps, eliminating the need for skilled manual configuration while maintaining high automation extent.
Solution Approach 2:
The system changes parameters by dynamically selecting different identification mechanisms (CSS selectors, XPath, etc.) based on the analyzed metadata of web page elements. This allows the same test framework to adapt to different UI structures without manual reconfiguration, resolving the contradiction between automation extent and operational ease.
2Reliability
If selectors are chosen based on current UI structure, then test automation works initially, but rapidly becomes outdated due to UI changes
Solution Approach 1:
The system implements dynamics by making selector selection adaptive rather than static. The interpreter algorithm dynamically analyzes metadata and chooses appropriate identification mechanisms based on the current state of web page elements, allowing the test automation to adapt to UI changes without becoming outdated. This resolves the contradiction between initial reliability and long-term adaptability.
Solution Approach 2:
The system uses feedback mechanisms where the interpreter algorithm continuously analyzes metadata about web page elements and adjusts selector selection accordingly. This feedback loop ensures that selectors remain reliable even as UI structures evolve, maintaining both reliability and adaptability simultaneously.
3Adaptability or versatility
If detailed interaction steps are specified manually, then test automation can handle complex elements, but requires significant expertise and time investment
Solution Approach 1:
The system performs self-service by automatically generating interaction steps for complex web page elements. The interpreter algorithm analyzes metadata and autonomously determines the necessary commands (clicks, inputs, selections, etc.), eliminating the need for manual specification of detailed interaction steps while maintaining the ability to handle complex elements effectively.
Solution Approach 2:
The system performs preliminary action by pre-defining interaction patterns in the interpreter algorithm that can be automatically applied to various element types. This preliminary configuration allows the system to handle complex elements without requiring time-consuming manual setup, resolving the contradiction between adaptability and time investment.
Data Source
AI summary
Test automation for a web page comprising specifying a number of tests for web page elements comprising specifying a test step for each of a number of web page elements on the web page. Each test step is stored as a metadata object containing a unique identifier for the web page, a unique identifier for the web page element to which the test step corresponds, and a required interaction for the web page element. A test step is selected to perform on a web page element, and the metadata for the element is extracted according to its unique identifier in the test step. An interpreter algorithm processes the metadata to determine what the web page element is, how best to identify the web page element, and commands to perform the required interaction and chooses a selector for the web page element. The test step is then executed.