Software Agent Scoring Using Chaos Testing for Launch Optimization

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Solution Overview

Problem

Existing systems face inefficiencies in launching multiple software applications due to unknown performance reductions and usage requirements, leading to suboptimal optimization.

Innovation Solution

A chaos engineering algorithm is employed to dynamically perturb data agents within a computing device, applying stress tests, monitoring responses, and calculating usage scores to identify and reject underperforming agents.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If multiple software applications are launched simultaneously without performance evaluation, then the launching process is simple and fast, but the system optimization and efficiency are reduced

Engineering Contradiction:

Improvelaunching efficiencyVSAvoidsystem optimization

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system performs preliminary monitoring of data agents during a baseline period before actual software launching occurs. This preliminary action establishes usage baselines and identifies underperforming agents in advance, allowing the system to optimize the launching process without real-time delays while maintaining both speed and reliability

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system automatically evaluates data agent performance through chaotic perturbation and stress testing without requiring external intervention. The data agents self-report their usage metrics, and the system autonomously identifies underperforming agents and adjusts launching decisions accordingly, improving both efficiency and optimization simultaneously

Inventive Principle:

Principle #25Self-service

2Reliability

If data agents are monitored and tested extensively before launching, then system optimization is improved, but the launching process becomes more complex and time-consuming

Engineering Contradiction:

Improvesystem optimizationVSAvoidlaunching process complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system creates a virtual copy of the data agent environment to perform chaotic perturbation and stress testing. By simulating various conditions in this virtual environment, the system can evaluate agent performance without affecting the actual launching process, thus maintaining simplicity while improving optimization

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The system applies chaotic perturbation and stress tests only to specific data agents that show potential issues or are critical to the launching process. Rather than extensively testing all agents, the system focuses resources on partial evaluation where it matters most, reducing overall complexity while maintaining optimization quality

Inventive Principle:

Principle #16Partial or excessive action

3Ease of operation

If traditional monitoring methods are used without chaotic perturbation, then the system is simpler to operate, but the measurement precision of data agent performance is reduced

Engineering Contradiction:

Improvesystem simplicityVSAvoidperformance measurement accuracy

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The system dynamically adjusts the level of chaotic perturbation applied to data agents based on their initial performance characteristics. Rather than using a fixed, complex monitoring approach for all agents, the system adapts its evaluation intensity, maintaining operational simplicity while achieving precise measurement of actual performance under varying conditions

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system implements feedback loops where data agents report their usage metrics in real-time during chaotic perturbation. This feedback mechanism allows the system to automatically adjust monitoring intensity and interpret performance data accurately without requiring complex manual analysis, thus maintaining ease of operation while improving measurement precision

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12536073B2Computer-based systems configured for dynamic performance scoring of software agents and methods of use thereof

Publication Date: 2026.01.27 CAPITAL ONE SERVICES LLC

AI summary

In some embodiments, the present disclosure provides an exemplary method that may include steps of identifying at least one computing specification image within a plurality of computing specification images; monitoring each data agent within the plurality of preinstalled data agents for a predetermined period of time to establish a data agent usage baseline associated with each data agent within the plurality of preinstalled data agents; utilizing a chaos engineering algorithm to dynamically perturb each data agent; calculating a usage test score for each data agent within the plurality of preinstalled data agents; calculating an overall data agent-specific usage score associated with each data agent within the plurality of preinstalled data agents based on the plurality of data agent-specific usage test scores; and rejecting at least one data agent within the plurality of preinstalled data agents from being utilized to launch the instance of the software application.