Software Defect Classification via Root Cause Analysis
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Solution Overview
Problem
Classifying defects in a software environment is ambiguous, leading to high costs and inefficiencies in Quality Assurance, as existing methods fail to accurately identify root causes, resulting in potential impacts on customer revenue and waste.
Innovation Solution
A method and system that receive defect data from various sources, analyze current and historical data using predefined rules to determine root causes, and classify defects into categories based on these causes, facilitating efficient root cause analysis and resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional defect classification methods are used in software quality assurance, then the process is simple and quick, but the classification is ambiguous and leads to high costs and inefficiencies
Solution Approach 1:
The patent segments the defect analysis process into multiple distinct modules: defect data reception module, current environment data reception module, historical environment data reception module, analysis module, and classification module. This segmentation allows each module to handle specific tasks independently, improving classification accuracy while managing system complexity through modular architecture.
Solution Approach 2:
The patent implements preliminary action by collecting and storing historical environment data and current environment data before defect analysis occurs. The system pre-processes environment information, maintains environment databases, and prepares classification rules in advance, enabling more accurate defect classification when defects are actually detected without performing all analysis steps from scratch.
2Measurement precision
If comprehensive root cause analysis is performed across software and environment, then defect classification accuracy improves, but time consumption and resource investment increase
Solution Approach 1:
The system performs preliminary actions by pre-collecting and storing environment data (both current and historical) in databases before defect analysis is needed. Classification rules are pre-defined and stored, allowing the analysis phase to quickly retrieve and apply relevant information rather than gathering data from scratch during defect investigation.
Solution Approach 2:
The patent uses copying by maintaining historical environment data as a reference copy that can be compared against current environment states. Instead of re-analyzing past defects, the system copies relevant historical information and classification rules to apply to current defect cases, significantly reducing analysis time while maintaining accuracy.
3Reliability
If detailed environment compatibility checks are performed, then defect detection accuracy improves, but the cost of quality and hardware investment increase
Solution Approach 1:
The patent extracts only the relevant environment factors and compatibility parameters that actually impact defect occurrence, rather than performing exhaustive checks of all possible environment aspects. The system identifies and extracts key environment variables from complex software environments, focusing analysis resources on the most critical compatibility factors.
Solution Approach 2:
The system applies parameter changes by dynamically adjusting the depth and scope of environment compatibility checks based on defect characteristics and historical data. Instead of always performing maximum-detailed analysis, the system modifies analysis parameters to match the specific defect context, improving reliability while reducing unnecessary resource consumption.
Data Source
AI summary
System and method for classifying defects occurring in a software environment are disclosed. In one embodiment, the method comprises receiving defect data from at least one data source. The defect data comprises the defects occurring in the software environment. The method further comprises receiving current data and historical data pertaining to the software environment from a current environment database and a historical environment database. The method further comprises analyzing the defect data based on the current data, the historical data, and one or more rules to determine at least one root cause causing the defects in the software environment. The method further comprises classifying each of the defects into one or more categories based on the at least one root cause.