Cross-Platform App Benchmarking for Platform Defect Detection
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Solution Overview
Problem
Software developers often face challenges in identifying and addressing performance issues with their applications due to unawareness of underlying hardware or platform defects, leading to inefficient and frustrating user experiences, with existing solutions requiring redundant efforts and lacking user control over data collection.
Innovation Solution
A computing system that analyzes application performance data across similar platforms, establishes benchmarks, and identifies performance discrepancies, recommending or automatically implementing fixes to improve application performance, while ensuring user consent and privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a software developer analyzes performance data from their own application only, then they can identify issues within their application, but they remain unaware of performance issues caused by hardware or platform defects that affect multiple applications
Solution Approach 1:
The patent combines performance data from multiple applications executed on the same computing platform into a unified analysis system. The performance analysis module aggregates metrics from different applications to identify common performance issues that indicate platform-level defects, enabling developers to detect hardware or OS problems that would be invisible when analyzing single applications in isolation.
Solution Approach 2:
The system segments performance analysis into application-specific metrics and platform-wide metrics. By separating individual application performance data from aggregated platform performance data, the system can identify which performance issues are application-specific and which are caused by underlying platform defects affecting multiple applications.
2Reliability
If multiple software developers independently resolve similar performance issues, then each developer can fix their application, but redundant efforts are wasted and development time is lost
Solution Approach 1:
The system implements a feedback mechanism where performance data from multiple applications is continuously collected and analyzed. When a platform-level defect is identified, the system provides feedback to affected developers about the common issue and its resolution status, preventing redundant debugging efforts and enabling developers to apply proven fixes across multiple applications.
Solution Approach 2:
The performance analysis system serves multiple developers and applications simultaneously, providing universal detection and resolution capabilities. A single platform defect detection benefits all affected applications and developers, eliminating the need for each developer to independently discover and resolve the same underlying issue.
3Measurement precision
If a developer lacks knowledge to resolve a performance issue, then the issue may be identified, but the application cannot be improved without external expertise
Solution Approach 1:
The system acts as an intermediary between performance issues and developers. The performance analysis module not only identifies performance issues but also provides automated recommendations and guidance for resolution. This intermediary function bridges the gap between issue detection and resolution, helping developers fix problems even when they lack specialized knowledge.
4Productivity
If performance data is collected without user control, then comprehensive performance analysis is possible, but user privacy and data control concerns arise
Solution Approach 1:
The system implements dynamic user control where performance data collection permissions can be adjusted by users at any time. Users can grant or revoke access to performance data for specific applications or entirely, and the system adapts its data collection behavior based on user preferences. This dynamic approach maintains comprehensive analysis capability while respecting user autonomy and privacy concerns.
Data Source
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AI summary
A system is described that obtains first performance data collected during execution of a first application at a first group of computing devices, determines, based on the first performance data, at least one metric for quantifying performance of the first application, and compares the at least one metric to a corresponding benchmark derived from second performance data collected during execution of one or more second applications at a second group of computing devices. Each of the one or more second applications being different than the first application. The system determines whether the at least one metric is within a threshold amount of the corresponding benchmark, and further determines, determines, based at least in part on the at least one metric is not within the threshold amount of the corresponding benchmark, a fix to the first application and outputs, for presentation at a developer device, an indication of the fix.