Automated GUI Truncation Detection via Pattern Matching
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Solution Overview
Problem
Manual detection of truncated graphical user interface (GUI) elements across various languages, operating systems, browsers, and resolutions is tedious, time-consuming, and expensive.
Innovation Solution
An automated information handling system that uses a pattern-matching algorithm to detect truncated text elements and a reconstruction engine to identify truncated non-text elements in GUIs by comparing them with expected or reconstructed copies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual detection of truncated GUI elements is performed, then detection accuracy can be maintained, but testing time and cost increase significantly
Solution Approach 1:
The system creates a reconstructed copy of the expected GUI layout and compares it with the actual rendered GUI. By generating a digital model of the expected interface and performing automated visual comparison, the system achieves both high detection accuracy and automated efficiency, eliminating the need for manual detection while maintaining precision.
Solution Approach 2:
The patent replaces manual visual inspection (mechanical human effort) with an automated image processing and comparison system. The system uses computational algorithms to detect truncated GUI elements, substituting human operators with automated software that can process multiple languages, operating systems, browsers, and resolutions simultaneously.
2Reliability
If manual detection is used to ensure comprehensive coverage across different environments, then detection thoroughness is maintained, but labor cost and time consumption increase
Solution Approach 1:
The system is designed to universally test GUI elements across multiple languages, operating systems, browsers, and resolutions simultaneously. A single automated testing framework performs what would otherwise require multiple manual testing sessions, achieving comprehensive coverage while dramatically improving productivity and reducing costs.
Solution Approach 2:
By creating and comparing reconstructed copies of expected GUI layouts across different environments, the system achieves comprehensive detection coverage automatically. The reconstruction engine generates expected outputs for various configurations, and the comparison algorithm identifies truncations across all tested environments without requiring manual intervention in each case.
3Productivity
If automated testing is implemented, then testing efficiency and coverage are improved, but system complexity increases
Solution Approach 1:
The system manages complexity by focusing on creating and comparing simplified reconstructed copies of GUI elements rather than attempting to replicate the entire rendering pipeline. This approach automates testing efficiently while keeping the system architecture manageable through targeted image processing and pattern matching.
Data Source
AI summary
An information handling system detects whether a text element in a graphical user interface is truncated by comparing the text element with an expected text element using a pattern-matching algorithm. The system also detects whether a non-text element in the graphical user interface is truncated by comparing the non-text element to a reconstructed copy of the non-text element.