Fault Change Locating via Text Similarity Analysis
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Solution Overview
Problem
Current methods for locating faults in software systems are inefficient, requiring technicians to manually aggregate user complaints and troubleshoot multiple changes, leading to prolonged troubleshooting times and increased workload.
Innovation Solution
A fault change locating method using natural language technology to associate user complaint texts with historical changes based on text similarity, allowing for rapid identification of fault-causing changes by calculating text similarities between user complaints and change descriptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual aggregation and troubleshooting of user complaints is used, then fault locating accuracy is improved, but troubleshooting time and workload increase significantly
Solution Approach 1:
The patent replaces the manual mechanical process of aggregating and analyzing user complaints with an automated text mining and natural language processing system. The system automatically extracts fault information from user complaints, matches them with change logs, and identifies root causes without human intervention, thus resolving the contradiction between accuracy and time consumption.
Solution Approach 2:
The system enables self-service fault locating by automatically processing user complaints and matching them with relevant changes. The fault locating system serves itself by autonomously analyzing text data, identifying patterns, and determining fault causes without requiring technician intervention for each complaint analysis.
2Reliability
If technicians troubleshoot multiple changes one by one, then comprehensive fault identification is achieved, but productivity decreases
Solution Approach 1:
The patent segments the fault locating process into distinct automated components: user complaint collection, text mining for fault information extraction, change log analysis, and matching algorithms. This segmentation allows parallel processing of multiple complaints and changes simultaneously, maintaining comprehensive identification while dramatically improving productivity.
Solution Approach 2:
The system performs preliminary actions by pre-processing and indexing change logs, categorizing historical changes, and preparing text mining models before faults occur. This preliminary preparation enables rapid fault locating when complaints arise, achieving both completeness and high productivity without troubleshooting changes one by one.
3Measurement precision
If extensive aggregation of user complaints is performed, then false reports are reduced, but processing complexity increases
Solution Approach 1:
The patent replaces complex manual aggregation and verification processes with automated text mining and natural language processing systems. These systems automatically analyze complaint patterns, identify false reports through textual analysis, and verify genuine faults without requiring complex manual processing procedures.
Solution Approach 2:
The system changes the parameters of complaint processing by transforming unstructured user complaints into structured text data with extracted features. This parameter transformation simplifies the aggregation process by converting qualitative complaint descriptions into quantifiable text metrics that can be automatically analyzed and compared.
Data Source
AI summary
Some implementations of the present specification disclose a fault change locating method and apparatus, a device, a medium, and a program product. The method includes: calculating a text similarity between a description text corresponding to each change in a change set within a determined time period of a complaint time corresponding to a user complaint text and the user complaint text; and determining whether the change in the change set is related to the user complaint text, and if the change in the change set is related to the user complaint text, determining the related change as a fault change corresponding to the user complaint text.