Application Benchmarking Metrics via Intermediary Data Aggregation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Application developers face challenges in obtaining real-time, detailed performance data across various mobile devices and operating systems, as user feedback often lacks context and does not provide comprehensive insights into application performance across different devices and services.
Innovation Solution
A method is introduced to generate benchmarking metrics for applications by collecting data from multiple devices, identifying similar applications based on criteria, and computing statistical values to provide reporting metrics to developers, allowing for comparison of performance without human intervention. This method uses servers to gather performance data, computes metrics like crash rates and latency, and dynamically reassesses groupings based on continuous data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If user feedback is collected to determine application performance issues, then developers can identify problems, but the feedback lacks real-time data and detailed measurements across different mobile devices and services
Solution Approach 1:
The patent introduces a server-based intermediary system that collects performance data from multiple sources including user feedback, automated monitoring agents, and service providers. This intermediary consolidates scattered data points into comprehensive performance reports that retain both detailed measurements and contextual information about device environments, user behaviors, and service conditions.
Solution Approach 2:
The system creates a universal performance measurement framework that works across diverse mobile devices, operating systems, and cloud services simultaneously. By establishing common metrics and data collection protocols that function universally across different platforms and services, the system enables detailed performance tracking without requiring device-specific implementations.
2Adaptability or versatility
If developers write applications for different mobile operating systems to grow with the industry, then application compatibility improves, but development complexity and effort increase significantly
Solution Approach 1:
The system enables developers to adapt applications to different mobile operating systems by dynamically adjusting configuration parameters rather than rewriting code. The performance measurement system identifies platform-specific parameters and provides automated recommendations for optimization, allowing single codebase deployment across multiple OSes with minimal adaptation effort.
Solution Approach 2:
The patent employs template-based application structures and performance optimization patterns that can be copied and adapted across different mobile operating systems. By creating reusable performance measurement and optimization templates that work across platforms, developers can replicate successful implementations without starting from scratch for each OS.
3Measurement precision
If detailed performance measurements are provided to developers, then application optimization can be improved, but the measurements are not useful without proper context about device and service conditions
Solution Approach 1:
The system performs preliminary contextual analysis and data enrichment before presenting performance measurements to developers. It automatically collects device specifications, operating system versions, network conditions, and service configurations in advance, then pre-processes this contextual information to be seamlessly integrated with performance metrics, eliminating the need for developers to manually gather context.
Solution Approach 2:
The patent implements a feedback loop where performance measurements are continuously correlated with contextual data from device sensors, service logs, and user interactions. This feedback mechanism automatically adjusts and refines the contextual information associated with each measurement, ensuring that developers receive performance data that is inherently contextualized and immediately actionable.
Data Source
AI summary
Some embodiments of the invention provide a novel method for generating benchmarking metrics for applications that execute on computing devices (e.g., mobile devices). In some embodiments, the method collects data from numerous devices regarding the execution of numerous applications on these devices. For each particular application in a set of applications, the method of some embodiments identifies a group of applications that are similar to the particular application based on a set of criteria. This identification is without human intervention in some embodiments. From the collected data, the method generates a first set of reporting metrics for the identified group of applications, and provides the generated first set of reporting metrics to the developer of the particular application. In some embodiments, the method also provides to the developer a similar set of reporting metrics that the method generates from the collected data for the particular application. In this manner, the developer can compare the performance of the particular application with other similar applications.