Device Configuration Management via Crowd-Sourced Similarity
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Solution Overview
Problem
Software application developers face challenges due to device fragmentation across various Android devices, where each device has unique features and settings, leading to ambiguity in documentation and the need for manual configuration, which is inefficient and incomplete, especially for new devices.
Innovation Solution
A method and system that detects errors in app execution, collects information, sends requests for new configuration settings, and updates settings based on similarity scores with other devices, using a device setting management system that includes crowd-sourced data to determine optimal settings for different devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If app developers manually configure settings for each device, then configuration accuracy for tested devices is improved, but the time and effort required increases significantly and new devices are not covered
Solution Approach 1:
The system pre-configures device profiles with optimal settings for various device types and characteristics. When a device is encountered, the system matches it to a pre-configured profile rather than requiring manual configuration from scratch, thus maintaining accuracy while reducing time investment.
Solution Approach 2:
The system creates virtual copies of device configurations based on device fingerprints and characteristics. Instead of manually configuring each unique device, the system copies and adapts proven working configurations from similar devices, ensuring accuracy while dramatically reducing configuration time and effort.
2Productivity
If developers test only top popular devices, then configuration effort is reduced, but coverage for other and new devices is insufficient
Solution Approach 1:
The system develops universal configuration profiles that can be applied across multiple device types and models. A single profile can serve multiple devices with similar characteristics, allowing the system to maintain high productivity while achieving broad device coverage including new and less popular devices.
Solution Approach 2:
The system uses device fingerprints and characteristics to dynamically adjust configuration parameters based on the specific device encountered. This allows configurations to be adapted for new devices by modifying parameters based on device similarities to known devices, thereby expanding coverage without proportionally increasing configuration effort.
3Reliability
If detailed device-specific configurations are created, then app performance on specific devices is improved, but system complexity and maintenance burden increase
Solution Approach 1:
The system segments device characteristics into discrete fingerprint attributes and organizes configurations hierarchically by device type, model, and characteristics. This segmentation allows the system to maintain detailed device-specific configurations while managing complexity through structured organization and reusable configuration templates.
4Manufacturing precision
If manual configuration updates are performed for each device, then configuration accuracy is maintained, but automation level and scalability are limited
Solution Approach 1:
The system implements feedback mechanisms where configuration results and device performance data are collected and used to automatically refine and update configuration profiles. This feedback loop maintains configuration accuracy while reducing the need for manual intervention, as the system learns and adapts automatically from accumulated data.
Solution Approach 2:
The system enables automatic self-configuration by matching devices to appropriate profiles based on device fingerprints and automatically applying the correct settings. This self-service capability maintains configuration accuracy while dramatically increasing automation levels and scalability, eliminating the need for manual configuration updates for each device.
Data Source
AI summary
A method and system for determining and updating configuration settings on a device are provided herein. In some embodiments, a method for updating configuration settings on a device may include detecting an error condition produced by executing an app on the device, collecting information associated with the error condition, the app and the device responsive to the detected error condition, sending a request for new configuration settings, wherein the request includes the collected information, receiving one or more new configuration settings in response to the request, and updating one or more configuration settings of at least one of the device or the app using the new configuration settings received.