NLP-Based Test Script Auto-Update for UI Changes
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Solution Overview
Problem
Existing software testing methods require significant manual intervention and resource allocation, especially when updating test scripts due to changes in software product versions, leading to inefficiencies and increased error rates.
Innovation Solution
The use of natural language processing systems to identify and update user interface elements in test scripts, allowing automated software testing to adapt to changes by querying the system for the most relevant elements and updating the script accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If test scripts are used to automate software testing, then testing efficiency and consistency are improved, but the scripts require substantial effort to develop and maintain when software updates occur
Solution Approach 1:
The system performs self-updating by automatically detecting UI element changes through screenshots and using NLP to generate updated test scripts without human intervention. The testing system serves itself by identifying broken references and correcting them autonomously
Solution Approach 2:
The system implements feedback loops where test execution results are analyzed to detect UI element changes, which then trigger automatic script updates. The system continuously monitors and adjusts test scripts based on feedback from actual software behavior
2Reliability
If manual updates are performed each time software is updated, then test script accuracy is maintained, but significant time and resources are required
Solution Approach 1:
The patent replaces manual mechanical updating processes with automated computational systems. NLP models and computer vision algorithms substitute human analysts, automatically detecting UI changes and generating script updates without human intervention
3Speed
If traditional automated testing is used, then execution speed is improved, but the system fails when UI elements change names or positions
Solution Approach 1:
The system dynamically adapts to UI changes by continuously monitoring software interfaces and automatically adjusting test scripts. Rather than being static, the testing system evolves with the software, detecting and responding to UI element changes in real-time
Solution Approach 2:
The NLP system acts as an intermediary between the testing framework and UI elements. It translates UI changes into appropriate script modifications, bridging the gap between static test scripts and dynamic software interfaces
Data Source
AI summary
Aspects of the disclosure include methods and systems for performing automated software testing. The method includes obtaining a test script for software, executing the test script, and determining that the test script includes an action that cannot be completed. The method also includes identifying elements of a user interface of the software, inputting, into a natural language processing system, a query including the action and the elements, and receiving, in response to the query, an identified element. The method further includes continuing the executing of the software by performing the action on the identified element and determining that an updated user interface includes an element associated with the action of the test script. The method also includes updating the test script by adding a new action to the test script based on a determination that the updated user interface includes the element associated with the action.