App Version Power Consumption Detection Across Software Releases
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems fail to effectively identify which version of an application is causing abnormal power consumption in electronic devices, leading to inefficient usage and potential device issues.
Innovation Solution
A method and system that establish a power consumption database for multiple application versions, analyze power consumption information, and generate prompts for abnormal power consumption states based on comparisons across versions, using statistical methods to determine and alert users to problematic versions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If application programs are updated to add new features or correct defects, then functionality and reliability are improved, but abnormal power consumption may occur
Solution Approach 1:
The system performs preliminary power consumption evaluation before fully deploying an application version by first installing it in a test environment, measuring its power consumption characteristics, and comparing against baseline data. This preliminary action prevents problematic versions from reaching production users.
Solution Approach 2:
The system establishes bidirectional communication between terminal devices and the server to continuously feed back power consumption data. Terminal devices report actual power consumption measurements, and the server provides version recommendations, creating a closed-loop feedback system that enables dynamic optimization.
2Measurement precision
If power consumption monitoring is implemented for all application versions, then detection precision is improved, but system complexity increases
Solution Approach 1:
The system divides power consumption monitoring into distinct segments: baseline version monitoring, test version evaluation, and production version verification. Each segment has specific monitoring objectives and methods, reducing overall system complexity while maintaining comprehensive coverage.
Solution Approach 2:
The server acts as an intermediary that centralizes the complex tasks of data collection, analysis, and version evaluation. Terminal devices only need to perform simple local measurements and communicate with the server, transferring computational complexity from distributed devices to a centralized system.
3Measurement precision
If multiple versions of application power consumption are evaluated, then identification accuracy of abnormal versions is improved, but time consumption increases
Solution Approach 1:
The system performs preliminary power consumption testing on application versions in a test environment before production deployment. This preliminary evaluation identifies potentially problematic versions early, preventing time-consuming rollbacks later and reducing overall evaluation time.
Solution Approach 2:
The system implements selective monitoring that focuses evaluation resources on versions with higher risk profiles or greater power consumption deviations. Rather than uniformly evaluating all versions with equal depth, the system applies partial action to low-risk versions and excessive action to high-risk versions, optimizing the time-accuracy tradeoff.
Data Source
AI summary
A method and a system for detecting an application program version with abnormal power consumption are provided. The method includes the following. A power consumption database of multiple versions of a target application is established. Power consumption information of a target version of the target application is obtained. According to the power consumption database and the power consumption information, whether the target version of the target application has a first abnormal power consumption state evaluated based on different versions of the target application is determined. In response to the first abnormal power consumption state, an abnormal power consumption prompt corresponding to the target version is generated.