Automated Crash Analysis System for Software Stack Trace Identification
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Solution Overview
Problem
Conventional methods for determining the source of software crashes are error-prone, time-consuming, and often inaccurate, as they rely on manual comparison of stack traces, which can lead to incorrect attribution of crash causes and delayed customer support.
Innovation Solution
An automated end-to-end system that analyzes crash reports, identifies culprit modules, and generates signature back traces, using a combination of automated analysis and graphical user interfaces to provide accurate and timely identification of crash sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual comparison of stack traces is used to determine crash sources, then human expertise can be applied to analyze complex cases, but the process becomes time-consuming and error-prone
Solution Approach 1:
The patent introduces an automated analysis system that acts as an intermediary between the crash data and human analysts. This system processes stack traces, generates similarity scores, and produces preliminary analysis results, thereby reducing the time burden on human experts while maintaining accurate identification of crash sources through automated pattern recognition and comparison algorithms
Solution Approach 2:
The patent replaces the manual mechanical process of comparing stack traces with an automated computational system. The system uses algorithms to automatically parse, compare, and analyze crash data, substituting human manual labor with machine-based processing that is both faster and more consistent, thereby reducing time loss while preserving measurement precision through systematic analysis
2Measurement precision
If manual analysis of stack traces is performed, then detailed examination of crash data is possible, but the process is tedious and often fails to yield accurate information
Solution Approach 1:
The patent implements a self-service automated analysis system that independently processes crash data without requiring continuous human intervention. The system automatically parses stack traces, compares them against known patterns, generates similarity scores, and produces analysis results, thereby eliminating the tedious manual work while maintaining high accuracy through systematic automated examination of crash data
Solution Approach 2:
The patent replaces the tedious manual mechanical process of stack trace analysis with an automated computational system. The system uses algorithms to automatically parse, compare, and analyze crash data, substituting human manual labor with machine-based processing that is both faster and more consistent, thereby improving productivity while preserving measurement precision through systematic analysis
3Reliability
If conventional manual methods are used to compare stack traces, then human judgment can be applied, but the process is error-prone and time-consuming
Solution Approach 1:
The patent introduces an automated analysis system that acts as an intermediary between the crash data and final conclusions. This system processes stack traces, generates similarity scores, and produces preliminary analysis results with high reliability, reducing the time burden on human experts while maintaining accurate identification of crash sources through automated pattern recognition and comparison algorithms
Solution Approach 2:
The patent replaces the manual mechanical process of comparing stack traces with an automated computational system. The system uses algorithms to automatically parse, compare, and analyze crash data, substituting human manual labor with machine-based processing that is both faster and more consistent, thereby reducing time loss while preserving reliability through systematic analysis
Data Source
AI summary
A computer-implemented method assessing the risk of a future crash occurring on a computer system is disclosed. Crash results are received from a crash analysis system. The crash results are analyzed, at a processor, to determine the likelihood of the future crash occurring on the computer system. Information regarding the likelihood of the future crash occurring on the computer system is provided to a user of the computer system.