Automated UI Difference Detection Across Environments
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Solution Overview
Problem
Testing computer applications across different environments, such as operating systems and browsers, is challenging due to user interface differences and the potential for human error from tedium and fatigue in detecting these variations.
Innovation Solution
A system and process that generate and compare object-level descriptions of user interfaces across various environments, using action trackers and difference analyzers to automate the detection of differences, reducing the burden on human testers and providing detailed reports.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual testing of user interfaces across different environments is performed, then human testers can detect differences, but productivity decreases and human error increases due to tedium and fatigue
Solution Approach 1:
The patent replaces the mechanical human testing process with an automated computer-based system that captures, compares, and analyzes user interface elements across different environments. The system uses software agents to automatically perform actions on applications and compare resulting UI states, eliminating manual repetition and associated fatigue while maintaining detection accuracy.
Solution Approach 2:
The testing system performs self-testing by automatically executing predefined actions on applications and comparing the results without requiring continuous human intervention. The system captures UI elements, generates comparisons, and identifies differences autonomously, allowing the testing process to serve itself and significantly improving productivity.
2Adaptability or versatility
If comprehensive testing across multiple environments is performed, then detection of user interface differences improves, but device complexity increases due to multiple test configurations
Solution Approach 1:
The patent implements a universal testing framework that can operate across multiple operating systems, browsers, and hardware configurations through a single integrated system. The test execution engine and comparison logic remain consistent while adapting to different environments, allowing the same testing infrastructure to handle diverse configurations without proportional increases in complexity.
Solution Approach 2:
The system introduces an intermediary layer consisting of standardized interfaces and abstraction mechanisms between the test execution engine and the diverse test environments. This intermediary handles environment-specific variations, allowing the core testing logic to remain simple while supporting multiple platforms through standardized communication protocols.
3Measurement precision
If detailed comparison of user interface elements is performed, then measurement precision improves, but difficulty of detecting and measuring increases due to complexity of interface variations
Solution Approach 1:
The patent segments the user interface into discrete, identifiable elements such as buttons, text fields, and graphical components. Each element is captured and compared independently, breaking down the complex task of analyzing entire interface variations into manageable units. This segmentation enables precise comparison of individual elements while simplifying the overall analysis process.
Solution Approach 2:
The system transforms visual user interface elements into standardized data structures with defined parameters such as position, size, text content, and element type. By converting graphical interfaces into structured parameters, the system enables automated comparison using defined metrics, reducing the difficulty of detecting and measuring interface variations while maintaining high precision.
Data Source
AI summary
A user-interface testing process involves generating plural display-data representations of a common subject for plural respective user-interface instances. The resulting display data is tracked for each of the application user-interface instances so as to generate respective object-level descriptions of the user interface instances. The object-level descriptions are compared to detect differences between the application user-interface instances.