Automated Screenshot Testing for Enterprise Desktop Applications
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Solution Overview
Problem
Managing and updating multiple desktop applications across enterprise desktops is cumbersome and time-consuming, particularly with periodic testing required for feature validation and system changes.
Innovation Solution
A system and method utilizing an application test agent, orchestration engine, evaluation engine, and window classification analysis engine to automate the testing of software applications on virtual or physical desktops, creating application recipes, capturing screenshots, and classifying modal windows to determine if issues can be resolved automatically or require user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual testing of applications on each desktop is performed, then testing accuracy and validation can be ensured, but time consumption and labor requirements increase significantly
Solution Approach 1:
The system enables automated self-testing of applications across multiple desktops without requiring manual intervention. The test agent automatically executes test cases, captures screenshots, classifies modal windows, and validates application behavior, allowing the system to test itself rather than requiring human operators to manually verify each application on each desktop.
Solution Approach 2:
The patent replaces manual mechanical testing operations with automated computational processes. Instead of human testers manually navigating and verifying applications, the system uses software-based automated testing agents that programmatically execute tests, capture visual data, process images through classification engines, and validate results automatically.
2Reliability
If periodic testing is repeated for each application upgrade or system change, then system reliability is maintained, but productivity and operational efficiency decrease
Solution Approach 1:
The system establishes continuous automated testing that runs periodically without interrupting normal operations. The test agent continuously monitors application behavior, executes test cases automatically, and provides ongoing validation ensures, maintaining system reliability while avoiding the productivity loss associated with manual re-testing after each upgrade or change.
Solution Approach 2:
The automated testing system implements continuous feedback loops where test results are immediately analyzed and reported. The classification engine processes modal window screenshots and provides real-time feedback on application behavior, allowing rapid detection and response to issues following upgrades or system changes, thereby maintaining reliability without requiring lengthy manual re-validation.
3Manufacturing precision
If comprehensive feature testing is performed on each application, then testing thoroughness is improved, but device complexity and system resource requirements increase
Solution Approach 1:
The testing system is divided into modular components: test agents deployed on individual desktops, centralized orchestration engines, classification engines for modal window detection, and result validation modules. This segmentation allows comprehensive testing to be distributed across multiple devices without concentrating all complexity in a single system, enabling thorough testing while managing overall system complexity through modular architecture.
Data Source
AI summary
A method is disclosed for testing launched applications on a desktop environment. The method captures a screenshot from the launched application. The screenshot may then be analyzed to determine whether it is a modal screenshot or a clean screenshot. In the event the screenshot is determined to be a modal screenshot, the modal screenshot may be classified, and, if classified, information may be sought to resolve the problem with the modal screenshot. In the screenshot is determined to be a clean screenshot, the clean screenshot is evaluated against stored reference screenshots to identify a match.