Application Health Impact Scoring via Baseline Comparison
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Solution Overview
Problem
Users face challenges in determining the impact of applications on computing device health before and after installation, as existing methods lack reliable information, leading to potential negative effects that may not be reversible by uninstalling the application.
Innovation Solution
A system and method that detect applications as they are downloaded, perform baseline and post-installation health evaluations, and compare results to determine the impact on system health, using unique identifiers and a backend server to calculate and normalize system-health-impact scores, allowing users to assess potential impacts before installation based on data from other systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users rely on vendor-supplied information about application impact, then installation process is simple, but the information is not reliable
Solution Approach 1:
The system performs self-diagnosis by automatically monitoring system health metrics before and after application installation, eliminating reliance on vendor claims. The application detector and health evaluator work together to objectively measure impact on processor usage, memory consumption, and system stability.
Solution Approach 2:
The system establishes a feedback loop by continuously monitoring system health metrics and comparing pre-installation baseline data with post-installation measurements. This feedback mechanism provides reliable information about actual application impact, enabling informed user decisions.
2Reliability
If users perform elaborate reviews of applications before installation, then information reliability improves, but time consumption increases
Solution Approach 1:
The system performs preliminary automated health evaluations and baseline measurements before installation, so that when installation occurs, the comparison data is already prepared. This eliminates the need for time-consuming manual reviews while maintaining high information reliability.
Solution Approach 2:
The system replaces manual review processes with automated electronic monitoring and analysis. Health evaluators automatically track system metrics, compare baselines, and generate impact assessments, substituting human time investment with efficient computational analysis.
3Ease of operation
If users wait until after installation to discover application impact, then installation simplicity is maintained, but system health damage may occur
Solution Approach 1:
The system establishes a health baseline before installation and prepares detection mechanisms in advance, enabling immediate post-installation comparison. This preliminary preparation ensures that harmful impacts are detected promptly rather than allowing damage to accumulate undetected.
Solution Approach 2:
The system implements immediate feedback by continuously monitoring system health metrics after installation and comparing them against pre-installation baselines. This real-time feedback enables users to identify and address harmful impacts before they significantly degrade system performance.
4Measurement precision
If the system performs detailed health evaluations before and after installation, then measurement precision improves, but device complexity increases
Solution Approach 1:
The system segments the health evaluation process into distinct functional modules: application detectors identify installed software, health evaluators measure specific metrics like processor and memory usage, and impact analyzers compare baseline and post-installation data. This segmentation enables precise measurements while managing complexity through modular design.
Solution Approach 2:
The health evaluator performs multiple functions using a unified framework: it monitors processor usage, memory consumption, system stability, and various performance metrics simultaneously. This multi-functionality achieves comprehensive precise measurement without proportionally increasing system complexity.
Data Source
AI summary
A computer-implemented method for determining whether an application impacts the health of a system may comprise detecting an application, performing a first system-health evaluation, allowing the application to install on the system, performing a second system-health evaluation after the application is installed on the system, and comparing the second system-health evaluation with the first system-health evaluation to determine whether the application impacted the health of the system. Exemplary methods for determining the potential impact of an application on the health of a system and for calculating a system-health-impact score for an application based on information gathered from a plurality of systems are also disclosed. Corresponding systems and computer-readable media are also disclosed.