Condensing Repetitive Log Violations via Master Grouping
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Solution Overview
Problem
Existing computer tools generate repetitive and complex error logs, making it difficult for human reviewers to diagnose and address multiple instances of the same violation across different components, leading to confusion and potential missed critical design issues.
Innovation Solution
A method that searches log files for violations, creates a database of discovered errors, groups them by master objects, and produces a condensed summary by extracting a single instance of each error and counting its occurrences, allowing for efficient review and debugging by presenting unique errors per component.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If computer tools generate detailed error logs for each violation instance, then complete error information is captured, but the complexity and volume of logs increase making them difficult to analyze
Solution Approach 1:
The patent merges multiple identical violation instances into a single consolidated log entry. Instead of listing each violation separately, the system groups violations by type and location, combining their counts into one entry. This reduces log complexity while preserving complete error information through the use of violation counts and hierarchical grouping by master objects and instances.
Solution Approach 2:
The patent segments the log analysis process into distinct phases: first identifying unique violation types, then grouping them by master objects, and finally organizing by instances. This segmentation allows the system to manage complex error information in a structured manner, presenting it in a hierarchical format that reduces apparent complexity while maintaining information completeness.
2Measurement precision
If all violation instances are listed individually in error logs, then complete diagnostic information is provided, but the time required for human reviewers to analyze logs increases
Solution Approach 1:
The patent combines multiple violation instances of the same type into single consolidated entries with counts. This merging approach maintains diagnostic precision by preserving all violation information while reducing the number of individual entries reviewers must examine. The hierarchical grouping by master objects and instances ensures that diagnostic precision is maintained while significantly reducing review time.
Solution Approach 2:
The patent extracts the essential diagnostic information (violation type, location, and count) from numerous individual violation instances and presents only this extracted information in the consolidated log. This extraction process removes redundant repetitive details while retaining the core diagnostic value, enabling faster analysis without loss of precision.
3Reliability
If error logs present multiple instances of the same violation, then all occurrences are documented, but confusion increases and critical design issues may be missed
Solution Approach 1:
The patent merges identical violation instances into consolidated entries that document all occurrences through counting. This merging maintains reliability by ensuring all violations are captured and counted, while simultaneously improving ease of operation by presenting the information in a non-repetitive, organized format that reduces confusion and highlights critical issues.
Solution Approach 2:
The patent segments violations into hierarchical groups by master objects and instances, with each segment containing consolidated information about violations of that type. This segmentation organizes the information in a way that maintains complete documentation reliability while making the logs easier to navigate and analyze, preventing critical issues from being lost in repetitive listings.
Data Source
AI summary
A method includes searching a plurality of lines of a log file for a violation of a defined condition; creating a database of all discovered violations; converting the database of all discovered to a list of output violations grouped by master; and producing a condensed summary of error messages, the producing including: searching for a selected error message; extracting a single instance or error message and load into a master log file; searching for all other examples at all levels of a hierarchical output of the list; writing a count of instances of the violation messages to the master log file; and presenting a single instance of the violations, and the count of that violation.