DAG-Based Device Parameter Testing System
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Solution Overview
Problem
Current techniques for adjusting device parameters, such as in computer games and software, require manual trial and error, leading to suboptimal settings and time-consuming processes for customers.
Innovation Solution
A system utilizing a directed acyclic graph (DAG) to determine and test device parameters, where nodes represent combinations of device parameters, and population values are associated with each node to identify optimal settings through a greedy algorithm, maximizing image quality while maintaining performance thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual parameter adjustment is used, then customers can control device settings, but the process becomes time-consuming and results in suboptimal settings
Solution Approach 1:
The system performs self-testing and self-configuration by automatically determining device parameters through DAG-based testing and population value analysis, eliminating the need for manual customer adjustment while achieving optimal settings
Solution Approach 2:
The system pre-determines optimal parameter combinations by conducting comprehensive DAG-based testing and population analysis before actual use, so that when the device is deployed, the parameters are already optimized without requiring customer trial and error
2Measurement precision
If comprehensive parameter testing is performed, then optimal settings are identified, but the complexity of the system increases
Solution Approach 1:
The parameter space is segmented into a directed acyclic graph where nodes represent specific parameter combinations and edges represent transitions, allowing systematic exploration of the parameter space without overwhelming complexity
Solution Approach 2:
Population values serve as an intermediary metric that guides the testing process by indicating which parameter combinations are most relevant to actual user bases, reducing the need to test all possible combinations equally
Data Source
AI summary
A system, method, and computer program product are provided for testing device parameters. In use, a plurality of device parameters is determined, utilizing a directed acyclic graph (DAG). Further, the determined plurality of device parameters is tested.