Intelligent Test Log Aggregation and Error Remediation
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Solution Overview
Problem
Current automation testing tools lack the ability to efficiently aggregate and analyze log files from multiple sources, providing no intuitive visualization or automated remediation of errors across complex software systems, leading to significant effort in error detection and prevention across application layers.
Innovation Solution
A system for intelligent automation of computer software testing log aggregation, analysis, and error remediation, which includes a client and server architecture that generates metadata, aggregates errors across diverse log files, and automatically generates remediation tasks, using APIs and message queues to provide actionable insights and user-friendly dashboards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple independent automation testing tools are used to test complex software systems, then testing coverage and reliability are improved, but the complexity of aggregating and analyzing log files from multiple sources increases significantly
Solution Approach 1:
The patent introduces an intermediary log aggregation system that sits between multiple automation testing tools and the analysis phase. This intermediary component standardizes log formats, centralizes log storage, and provides unified analysis capabilities, thereby reducing the complexity of handling logs from multiple sources while maintaining comprehensive testing coverage
Solution Approach 2:
The log aggregation system is designed with universal capabilities to handle logs from various automation testing tools through a single interface. It provides multi-functional features including log collection, standardization, storage, analysis, and visualization, eliminating the need for separate handling mechanisms for each tool
2Measurement precision
If manual parsing and consolidation of individual log files is performed to identify errors, then detailed error analysis is achieved, but significant time and effort are consumed
Solution Approach 1:
The system implements automated self-service capabilities where the log aggregation system automatically parses, consolidates, and analyzes log files without requiring manual intervention. It employs automated error detection algorithms, pattern recognition, and intelligent filtering to identify and prioritize errors, thereby achieving detailed error analysis while significantly reducing the time and effort required
Solution Approach 2:
The patent replaces the mechanical manual process of parsing and consolidating log files with an automated computational system. This system uses computer-based algorithms, machine learning models, and automated scripting to perform error detection and consolidation tasks that were previously done manually, thereby maintaining precision while reducing time consumption
3Loss of information
If comprehensive error analysis across multiple log files is performed, then complete error identification is achieved, but the difficulty of visualizing and understanding the entire automation tool execution process increases
Solution Approach 1:
The patent applies segmentation by dividing the comprehensive error analysis into organized categories and hierarchical levels. It segments errors by type, severity, source tool, and affected software component, providing structured visualization that maintains complete error identification while making the information manageable and understandable through organized presentation
Solution Approach 2:
The system introduces additional visualization dimensions such as temporal sequences, hierarchical structures, and multi-layered dashboards to present error data. It transforms complex error information into visual representations across different dimensions (time, priority, source, impact), enabling complete error identification to be visualized in an intuitive and comprehensible manner
4Productivity
If automated remediation tasks are generated based on error analysis, then productivity is improved, but the extent of automation required increases system complexity
Solution Approach 1:
The system performs preliminary actions by pre-configuring remediation templates, automation rules, and response protocols for common error types. It establishes predefined workflows and remediation strategies in advance, allowing automated remediation tasks to be generated quickly based on matched patterns, thereby improving productivity while managing automation complexity through preparation
Solution Approach 2:
The patent employs parameter changes by dynamically adjusting automation levels, remediation thresholds, and task priorities based on error characteristics and system state. It modifies automation parameters flexibly to balance productivity gains with complexity management, enabling selective automation that targets high-value opportunities while maintaining manageable system complexity
Data Source
AI summary
Methods and apparatuses are described for intelligent automation of computer software testing log aggregation, analysis, and error remediation. A client device generates test log files for software automation testing tools, each test log file comprising errors generated by execution of test scripts. The client device creates an archive file with the log files and transmits the files to a server. The server extracts the files from the archive file and parses each of the files to identify errors. The server aggregates errors from at least two of the files and transmits the aggregated errors to a log management message queue and a development message queue. The server generates a user interface and transmits the user interface to a remote device. The server also generates development change orders that, when executed by the server, create tasks in a development tracking system to resolve errors by changing development source code.