Automated Defect Classification System for Software Patch Assessment

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Solution Overview

Problem

Manual categorization of software defects is time-consuming, prone to errors, and inefficient, especially for large projects, as it requires substantial resources and can lead to repeated re-categorization due to changing patterns and trends over time, making it difficult to determine patch availability and upgrade strategies for customers across various platforms and operating systems.

Innovation Solution

A method and system for automatically classifying defects using a computer program that receives information about a client system, applies reasoning rules to analyze data, and provides expert assessments on patch status and upgrade strategies, optimizing the process by utilizing databases and knowledge bases to mimic expert decision-making.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual categorization of software defects is performed, then expert assessment and defect classification can be achieved, but the process becomes time-consuming and resource-intensive

Engineering Contradiction:

Improvedefect classification accuracyVSAvoidcategorization time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces the mechanical manual categorization process with an automated computer-based system that uses machine learning models and algorithms to classify defects, thereby eliminating the time-consuming manual effort while maintaining or improving classification accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service automated defect categorization where the computer program independently analyzes defect data, applies classification rules, and generates assessments without requiring human intervention for each defect, thus reducing both time and resource burden

Inventive Principle:

Principle #25Self-service

2Reliability

If manual defect categorization is performed, then defect patterns can be identified, but errors and inconsistencies increase

Engineering Contradiction:

Improvedefect assessment reliabilityVSAvoidcategorization accuracy

Core Design Contradiction:

ReliabilityVSMeasurement precision

Solution Approach 1:

The patent replaces manual human judgment with automated computer-based analysis that consistently applies predefined rules and machine learning models, eliminating human errors and inconsistencies while improving the reliability and precision of defect categorization

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system incorporates feedback mechanisms where classification results are continuously refined based on analyzed defect patterns and outcomes, improving the reliability and accuracy of assessments over time through iterative learning and rule optimization

Inventive Principle:

Principle #23Feedback

3Loss of information

If comprehensive defect analysis is performed manually, then complete defect information can be gathered, but the complexity and resource requirements increase substantially

Engineering Contradiction:

Improvedefect information completenessVSAvoidsystem complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent replaces complex manual analysis processes with automated computer programs that systematically gather, process, and analyze comprehensive defect information from multiple sources, maintaining information completeness while reducing operational complexity and resource requirements

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system employs multi-functional computer programs that can handle various defect analysis tasks, data sources, and classification scenarios within a single unified platform, reducing overall system complexity while maintaining comprehensive information gathering capabilities

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Reliability

If manual defect tracking is performed, then defect patterns can be monitored, but productivity and efficiency decrease

Engineering Contradiction:

Improvedefect pattern detection reliabilityVSAvoiddefect analysis productivity

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent replaces manual defect tracking with automated computer-based monitoring systems that continuously analyze defect data, identify patterns, and generate assessments at high speed, thereby dramatically improving productivity while maintaining or enhancing the reliability of pattern detection through consistent rule application

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS9454727B2Methods, systems, and computer program product for implementing expert assessment of a product

Publication Date: 2016.09.27 ORACLE INT CORP

AI summary

Disclosed are method(s), system(s), and computer program product(s) for implementing expert assessment of a product. Some embodiments are directed at improved methods, systems, and computer program product form implementing expert assessment of product fixes/patches or upgrade. In some embodiments, the method or the system identifies or receives information regarding a client system on which the product runs and a reasoning rule for the expert assessment; analyzes the received or identified information based upon the reasoning rule; and determines the expert assessment based on the result of the act of analyzing the information. In some embodiments, the method or the system further comprises optimizing the expert assessment based on other information; determining whether the determination of the expert assessment is deterministic; and determining whether or not there exists a conflict in the expert assessment.