Decentralized AI Self-Healing for Distributed Software Errors

Solution Overview

Problem

Existing software systems face challenges in detecting and automatically repairing errors, particularly logic and syntax errors, which can lead to application failures affecting multiple applications and servers, and are compounded in enterprise environments with multiple deployments across different regions, making error detection and management difficult.

Innovation Solution

A decentralized control system using artificial intelligence, specifically machine learning models like large language models (LLMs), to detect software errors, generate solutions, and deploy updates autonomously, minimizing downtime by identifying and fixing errors before they impact other applications and servers.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual error detection and repair methods are used, then developers can identify and fix software errors, but the process is time-consuming and errors may spread to multiple applications and servers before detection

Engineering Contradiction:

Improvesoftware error detection capabilityVSAvoiderror detection and repair time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system implements self-service through autonomous agents that automatically detect, diagnose, and repair software errors without human intervention. The agents monitor application behavior, identify anomalies, and execute repairs autonomously, enabling the system to heal itself and eliminating the time delay associated with manual error detection and repair.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system performs preliminary action by proactively monitoring applications for error conditions before they can spread to other systems. The autonomous agents continuously analyze application behavior and detect potential issues early, allowing repairs to be made before errors propagate across the enterprise environment, thus preventing cascading failures.

Inventive Principle:

Principle #10Preliminary action

2Adaptability or versatility

If decentralized architecture with multiple application instances is deployed across different regions, then system availability and scalability are improved, but error detection and management become more complex and difficult

Engineering Contradiction:

Improvedeployment flexibility across regionsVSAvoiderror detection and management complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system applies segmentation by dividing the error detection and management function into independent autonomous agents deployed at each regional location. Each agent operates independently to monitor and repair errors in its local environment, eliminating the need for centralized error management and reducing the complexity of managing errors across distributed systems while maintaining deployment flexibility.

Inventive Principle:

Principle #1Segmentation

3Ease of repair

If traditional error repair methods are used, then errors can be fixed after detection, but downtime is significant and other applications may be affected before repair

Engineering Contradiction:

Improvesoftware error repair capabilityVSAvoidapplication downtime

Core Design Contradiction:

Ease of repairVSDuration of action of moving object

Solution Approach 1:

The system implements self-service through autonomous agents that automatically detect, diagnose, and repair software errors without human intervention. The agents monitor application behavior, identify anomalies, and execute repairs autonomously, enabling the system to heal itself and eliminating the time delay associated with manual error detection and repair.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system performs preliminary action by proactively monitoring applications for error conditions before they can spread to other systems. The autonomous agents continuously analyze application behavior and detect potential issues early, allowing repairs to be made before errors propagate across the enterprise environment, thus preventing cascading failures.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20260029997A1Decentralized architecture using artificial intelligence driven autonomous self-healing of distributed software

Publication Date: 2026.01.29 AMERICAN EXPRESS TRAVEL RELATED SERVICES CO INC

AI summary

Disclosed herein are system, method, and computer program product embodiments for autonomously repairing software by leveraging a large language model (LLM). A control system may detect a first error associated with an application executing in a region. The control system may then repair the first error associated with the application by: identifying a source of the first error within the application; generating a solution by inputting the source of the first error to an LLM; and implementing the solution via the LLM. The control system may then determine that the application is repaired by: executing the application; generating an output; and comparing the output to a predefined value. The control system may then deploy the application in the region.