Automated Defect Diagnosis via Signature Querying
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Solution Overview
Problem
Technical support personnel face inefficiencies and high costs due to manual review of system data to diagnose and resolve defects, as they must search through diagnostic data based on rough customer descriptions.
Innovation Solution
An automated support system that processes system diagnostic data to generate defect signatures, allowing for query-based identification of defects and subsequent remediation, utilizing a diagnostic engine to perform queries against structured records and output remediation information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If technical support personnel manually review system diagnostic data to identify defects, then defect diagnosis can be performed, but the process is inefficient and costly
Solution Approach 1:
The system enables self-service defect diagnosis by automatically analyzing system diagnostic data and generating defect signatures without requiring manual intervention. The automated support system processes diagnostic data, identifies defects, and provides remediation information, allowing the system to serve itself rather than requiring technical support personnel to manually review each case.
Solution Approach 2:
The patent replaces the mechanical manual review process with an automated computational system. Instead of technical support personnel manually searching through diagnostic data, the system uses automated defect signature generation and querying mechanisms to identify defects, substituting human manual labor with automated information processing.
2Reliability
If technical support personnel manually search through diagnostic data based on rough customer descriptions, then defects can be identified, but the process is costly
Solution Approach 1:
The patent segments the defect identification process into distinct automated components: defect signature generation from system diagnostic data, defect signature querying, and remediation information retrieval. This segmentation transforms the complex manual search process into structured, automated steps that can be executed systematically without human intervention.
Solution Approach 2:
The system introduces defect signatures as an intermediary between customer descriptions and defect identification. Instead of requiring technical support personnel to directly interpret rough customer descriptions and search through diagnostic data, the system uses automatically generated defect signatures as a mediating layer that bridges the gap between customer input and accurate defect identification.
3Ease of operation
If automated defect diagnosis is implemented, then time and effort are reduced, but system complexity increases
Solution Approach 1:
The automated support system is designed as a universal platform that handles multiple functions: processing system diagnostic data, generating defect signatures, querying defects, and providing remediation information. This multi-functional design consolidates what would otherwise require multiple separate tools or manual processes into a single integrated system, making defect diagnosis easier while managing complexity through consolidation.
Data Source
AI summary
Diagnosis of defect(s) in a system is disclosed. A defect signature-based query is performed against system diagnostic data stored in one or more structured records. It is determined that a defect signature is associated with a system based at least in part on the query. Remediation information generated based at least in part on the defect signature and the system diagnostic data may be output.