Crash Dump Analysis Automation for Root Cause Remediation

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Solution Overview

Problem

Conventional manual processes for handling system crashes in IT infrastructure are inefficient, requiring significant human intervention, specialized skills, and result in prolonged downtime, productivity loss, and increased costs due to the inability to analyze crash dump files at scale.

Innovation Solution

An automated system crash analysis tool that monitors for designated event types, copies system crash log files to a database, generates analysis data structures, and applies remedial actions to reduce the likelihood of future crashes, eliminating human dependency and enabling bulk analysis of crash dump files.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual processes are used to analyze system crash dump files, then specialized human skills and intervention are required, but analysis time is prolonged and productivity is reduced

Engineering Contradiction:
Improvecrash analysis accuracyVSAvoidanalysis throughput
Core Design Contradiction:
Measurement precisionVSProductivity

Solution Approach 1:

The system enables automated self-analysis of crash dump files through machine learning models and automated remediation processes, eliminating the need for manual human intervention while maintaining high accuracy in identifying crash causes and applying appropriate fixes

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The patent replaces manual human analysis processes with automated computational systems including machine learning models and automated remediation engines, substituting human cognitive work with algorithmic processing to achieve both high accuracy and scalability

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If manual analysis of crash dump files is performed, then specialized skills are utilized, but significant human intervention and time are required

Engineering Contradiction:
Improvecrash diagnosis accuracyVSAvoiddowntime
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary automated analysis of crash dump files immediately when crashes occur, using pre-trained machine learning models to quickly identify root causes before systems are taken offline, thereby reducing downtime while maintaining diagnostic accuracy

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

Manual diagnostic processes are replaced with automated machine learning-based analysis systems that can rapidly process crash dump files and identify root causes without requiring human expert intervention, significantly reducing the time from crash occurrence to diagnosis

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If conventional manual processes are used for crash handling, then human expertise is applied, but the inability to analyze crash dump files at scale increases costs

Engineering Contradiction:
Improvecrash cause identification accuracyVSAvoidnumber of analyzable events
Core Design Contradiction:
Measurement precisionVSQuantity of substance

Solution Approach 1:

The automated system provides universal analysis capabilities that can handle any type of system crash across multiple platforms and device types using the same machine learning models and remediation frameworks, enabling scale analysis of crash events without requiring specialized human expertise for each case

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent replaces manual human analysis processes with automated computational systems including machine learning models and automated remediation engines, substituting human cognitive work with algorithmic processing to achieve both high accuracy and scalability

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

4Productivity

If automated analysis is implemented, then analysis speed and scale are improved, but system complexity increases

Engineering Contradiction:
Improveanalysis throughputVSAvoidautomation system complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The system introduces an automated remediation engine as an intermediary layer that coordinates between crash detection, machine learning analysis, and remediation application, managing the complexity of the automated workflow through a centralized control mechanism

Inventive Principle:
Principle #24Intermediary (Mediator)

Data Source

PatentUS12547489B2Automated system crash analysis and remediation
Publication Date: 2026.02.10 DELL PROD LP
  • US12547489B2 patent drawing
  • US12547489B2 patent drawing
  • US12547489B2 patent drawing

AI summary

An apparatus comprises at least one processing device configured to monitor for designated system crash event types and, responsive to detecting at least one designated system crash event type on a first information technology (IT) asset, to copy system crash log files from the first IT asset and to process the copied system crash log files to generate a first crash dump analysis data structure associated with the first IT asset. The at least one processing device is further configured to generate, based at least in part on the first crash dump analysis data structure and additional crash dump analysis data structures associated with additional IT assets, a system crash root cause analysis data structure. The at least one processing device is further configured to apply remedial actions, selected based at least in part on the system crash root cause analysis data structure, to a plurality of IT assets.