Global Error-Code Sequence for Knowledge Document Indexing
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Solution Overview
Problem
Current software development systems face challenges in efficiently correlating error conditions in log files with relevant knowledgebase documents due to dynamic code changes, leading to increased downtime and maintenance costs.
Innovation Solution
The implementation of a Global Error-Code Sequence (GECS) system that generates unique error codes, linking error conditions with knowledgebase documents, allowing for automated indexing and improved search functionality within knowledge management systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional log file analysis methods are used in dynamic software development environments, then software updates and new features can be deployed rapidly, but correlating error conditions with knowledgebase documents becomes increasingly difficult and time-consuming
Solution Approach 1:
The system pre-generates globally unique error codes for potential error conditions before they actually occur in the software. These error codes are embedded in the codebase in advance, so when an error occurs, the pre-existing code can immediately capture and report it, eliminating the need to create and correlate error information in real-time during rapid software updates.
Solution Approach 2:
The patent introduces globally unique error codes as an intermediary between error conditions in the software and the knowledgebase documents. These error codes serve as stable identifiers that bridge the dynamic software environment and the static knowledgebase, enabling efficient correlation without requiring complex real-time analysis of log files.
2Reliability
If comprehensive log files are collected for diagnostic purposes, then error investigation capability is improved, but the volume of data to be managed and analyzed increases significantly
Solution Approach 1:
The system extracts the essential error identification function from voluminous log files by implementing globally unique error codes that are embedded directly in the software. Instead of collecting and analyzing large volumes of log data to identify errors, the system extracts only the critical error code information that directly points to the specific error condition and its corresponding knowledgebase document.
Solution Approach 2:
The patent creates simplified copies of error information in the form of globally unique error codes that are embedded in the software codebase. These error code copies contain the essential identification information needed for error diagnosis, replacing the need to analyze comprehensive log files while maintaining reliable error investigation capability.
3Adaptability or versatility
If manual error code management is used in enterprise systems, then flexibility in handling diverse error conditions is maintained, but maintenance costs and complexity increase
Solution Approach 1:
The system implements a universal globally unique error code framework that can handle diverse error conditions across the entire enterprise software ecosystem. This single standardized approach provides multi-functionality, serving as both an error identifier and a direct link to knowledgebase documents, eliminating the need for separate manual management processes for different types of errors.
Solution Approach 2:
The error code system is designed to be self-generating and self-managing through automated processes. The globally unique error codes are automatically generated and embedded in the software during compilation, and the system automatically correlates errors with knowledgebase documents, eliminating the need for manual error code management while maintaining high adaptability.
Data Source
AI summary
Disclosed embodiments provide techniques for generating and using a Global Error-Code Sequence (GECS), with the role of generating, at request, a unique error identification number (ID). The scope of the unique identification number can include worldwide, company-wide, or a certain application ecosystem, such as eCommerce applications, etc. The GECS forms a strong correlation between an error condition and a known solution. While other logging signatures such as line numbers, stack traces, and addresses can change with new releases or invocations, the GECS enables a tighter coupling between an error condition and a knowledgebase document, which enables faster resolution of computer application problems and reduced downtime.