AR Test Case Generation via Event-Flow Graphs
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Solution Overview
Problem
The sheer number of possible interactions with virtual objects in augmented reality (AR) environments poses challenges for effectively and efficiently testing AR applications.
Innovation Solution
A method is developed to generate test cases by constructing a virtual object hierarchy and an event-flow graph, identifying paths of events, and storing these as test cases for subsequent testing of AR applications, utilizing an AI-based algorithm to reduce infeasible paths and focus on optimal testing sequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional testing methods are used for AR applications, then testing can be performed manually, but the sheer number of possible interactions with virtual objects makes it inefficient and incomplete
Solution Approach 1:
The system automatically generates test cases by analyzing the AR application's virtual object hierarchy and event-flow graphs without requiring manual intervention. The processor device autonomously constructs the object hierarchy, identifies events, generates event-flow graphs, and creates test cases, enabling the testing system to serve itself and eliminate manual testing bottlenecks.
Solution Approach 2:
The patent replaces manual mechanical testing processes with an automated computational system. Instead of manually exploring and testing each interaction, the system uses algorithmic generation of event-flow graphs and automated path identification to substitute human effort with computational processes, dramatically improving testing efficiency.
2Reliability
If all possible interactions are tested manually, then comprehensive coverage might be achieved, but the time and resources required become prohibitive
Solution Approach 1:
The system performs preliminary analysis by constructing the virtual object hierarchy and identifying all possible events before generating test cases. By pre-analyzing the application structure and potential interactions, the system prepares a comprehensive test framework in advance, ensuring complete coverage while reducing actual testing time through automated execution of pre-planned test sequences.
Solution Approach 2:
The system creates simplified representations (copies) of the AR application's object hierarchy and event flows in the form of event-flow graphs. These graphical models serve as compressed representations that capture all possible interactions without requiring actual execution of each interaction, allowing comprehensive analysis and test case generation without proportionally increasing testing time.
3Ease of operation
If manual testing is used to handle complex virtual object interactions, then flexibility in testing approach is maintained, but the complexity of managing numerous interaction scenarios increases
Solution Approach 1:
The event-flow graph serves as an intermediary representation between the complex virtual object hierarchy and the test case generation process. This graphical model mediates by providing a simplified, visual representation of event sequences and object interactions, making it easier to analyze and generate test cases without directly managing the full complexity of the original AR application's virtual objects.
Solution Approach 2:
The system segments the complex AR application into a hierarchical structure of virtual objects, where each object and its events are analyzed independently. By dividing the application into discrete, manageable components (virtual objects and their associated events), the system reduces the complexity of managing all interactions at once while maintaining comprehensive coverage through systematic combination of segmented elements.
Data Source
AI summary
Generating test cases for augmented reality (AR) application testing is disclosed. In one embodiment, an AR computing device constructs a virtual object hierarchy comprising a plurality of nodes corresponding to a plurality of virtual objects of a test AR environment. The AR computing device next generates an event-flow graph based on the virtual object hierarchy, wherein the event-flow graph comprises a directed graph comprising a plurality of vertices, wherein each vertex corresponds to an event supported by a virtual object of the plurality of virtual objects, and a plurality of edges, wherein each edge connects two (2) vertices of the plurality of vertices. The AR computing device then identifies a plurality of paths based on the event-flow graph, wherein each path comprises one or more edges of the plurality of edges. The paths are then stored as a plurality of test cases (e.g., for use as input during subsequent testing).