Automated Session Analysis for Technical Error Resolution
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Solution Overview
Problem
Debugging technical issues in computer systems can be time-consuming and challenging, especially in environments where users lack the time to report problems due to the complexity of reproducing issues and the need for extensive troubleshooting processes.
Innovation Solution
A method involving a user interface that records user interactions and audio explanations, which are then processed by a machine learning model to provide potential solutions, including the removal of sensitive information and formatting data for analysis, to expedite issue resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional debugging methods are used, then problem resolution can be achieved, but the time and effort required for troubleshooting increases significantly
Solution Approach 1:
The system enables self-service debugging by automatically analyzing session records and generating potential solutions without requiring extensive manual intervention from users or support personnel. The machine learning model processes the recorded data and provides diagnostic recommendations autonomously.
Solution Approach 2:
The system performs preliminary analysis by recording user sessions and preparing the data for analysis in advance. This preliminary action captures all necessary information during normal operation, so that when an issue occurs, the analysis can proceed immediately without requiring time-consuming reproduction of the problem.
2Loss of information
If users report technical issues with detailed information, then problem diagnosis improves, but users lack time to provide comprehensive reports due to primary responsibilities
Solution Approach 1:
The system automatically collects and analyzes session records without requiring users to manually provide diagnostic information. The recording captures user actions, system responses, and contextual data automatically, eliminating the need for users to document problems while maintaining comprehensive diagnostic information.
Solution Approach 2:
The session recording system acts as an intermediary that automatically captures and preserves diagnostic information that would otherwise require user effort to provide. The recording mediates between the user's limited time and the need for comprehensive problem information by autonomously documenting all relevant details.
3Measurement precision
If session records are analyzed in detail, then accurate solutions can be provided, but processing time increases
Solution Approach 1:
Session records are captured and prepared in advance during normal system operation. This preliminary action ensures that when analysis is needed, the data is already organized and ready for processing, reducing the time required for detailed analysis while maintaining accuracy.
Solution Approach 2:
The system replaces manual analysis methods with automated machine learning-based analysis. This substitution enables rapid processing of detailed session records while maintaining or improving solution accuracy, as the automated system can analyze comprehensive data without the time constraints of manual review.
Data Source
AI summary
Methods, systems, and storage media including instructions for resolving technology issues is described. One of the methods includes receiving, by at least one processor, a session record of user producing a technical error on a computer system. The method includes providing, by the at least one processor, the session record for resolution to a processing system. The method also includes providing, by the at least one processor, a potential solution to the technical error.