Automated Software Script Remediation via UI Object Similarity
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Solution Overview
Problem
Existing software automation scripts face inefficiencies and maintenance downtime due to issues with identifying user interface (UI) objects, particularly when web page objects change, leading to manual intervention and delays.
Innovation Solution
A method for real-time remediation that calculates similarity scores between UI objects and historical data to automatically identify and modify the script, allowing it to adapt to changes by replacing the original UI object with a similar one, using techniques like edit distance, Cosine similarity, or machine learning models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated testing scripts are used to test software applications, then testing efficiency is improved, but the scripts fail when UI objects change requiring manual intervention
Solution Approach 1:
The system enables automated self-healing where the script automatically identifies similar UI objects when original objects change and modifies itself to adapt to the changes. The remediation system calculates similarity scores between current and historical UI objects, automatically selects the best match, and updates the script without human intervention, allowing the script to service itself during changes.
Solution Approach 2:
The system changes the identification parameters of UI objects by calculating similarity scores based on multiple attributes (location, size, color, text content) and using these scores to determine which object should replace the failed identification. This parameter-based approach allows flexible adaptation to UI changes while maintaining script functionality.
2Manufacturing precision
If manual intervention is required to update scripts when UI objects change, then script accuracy is maintained, but maintenance time increases
Solution Approach 1:
The remediation system performs self-service by automatically calculating similarity scores, identifying the best matching UI object, and modifying the script without requiring manual intervention. This eliminates the time-consuming manual process while maintaining accuracy through automated comparison of multiple object attributes.
Solution Approach 2:
The system performs preliminary actions by pre-calculating and storing historical UI object data and characteristics before changes occur. When changes happen, this pre-prepared historical data enables immediate similarity calculations and automatic remediation, avoiding the need for manual analysis and reducing maintenance time.
3Measurement precision
If scripts are manually updated when UI objects change, then identification accuracy is maintained, but productivity decreases
Solution Approach 1:
The system enables self-service remediation where the script automatically maintains identification accuracy by calculating similarity scores and selecting the best matching UI object without manual intervention. This automated process maintains the same level of precision as manual updates while dramatically improving productivity by eliminating maintenance downtime.
Data Source
AI summary
A method for real-time remediation of a software script includes, during execution of the script, attempting to identify a first user interface (UI) object. In response to failing to identify the first UI object, similarity scores are calculated based on the data of the plurality of UI objects and historical data associated with the first UI object. A second UI object is identified, from the plurality of UI objects, based on the calculated similarity scores. The script and/or an object repository referenced by the script are then automatically modified so that subsequent execution of the script includes attempting to identify the second UI object instead of the first UI object.