Risk-Based Software Testing Framework for Defect Evaluation
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Solution Overview
Problem
Current methods for predicting and managing defect-related risks in software systems are inadequate, as they are static, subjective, and fail to consider multiple levels of a hierarchical structure, leading to inconsistent and incomplete risk evaluations, especially in complex software development cycles.
Innovation Solution
A systematic and disciplined approach is implemented using a risk analysis system that defines orthogonal risk contexts, associates risk factors with these contexts, and dynamically updates risk based on actual test results, enabling comprehensive and adaptable risk-based testing across all levels of the software development lifecycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional static and subjective risk assessment methods are used, then the implementation is simple, but the risk evaluation consistency and completeness deteriorate
Solution Approach 1:
The patent segments the software system into a hierarchical structure with multiple levels (system level, subsystem level, component level). Each level has its own risk contexts and factors that can be independently assessed. This segmentation enables consistent risk evaluation across different granularities while maintaining manageable complexity at each level.
Solution Approach 2:
The patent transforms subjective risk assessments into objective evaluations by changing the parameters from qualitative judgments to quantitative measurements. Risk factors are assigned numerical values and weights, and risk scores are calculated using mathematical formulas. This parameter change ensures consistency and repeatability while the structured framework controls the complexity of the assessment process.
2Reliability
If comprehensive testing is performed at all software development stages, then defect detection capability is improved, but time and resource consumption increase
Solution Approach 1:
The patent enables preliminary risk assessment at early software development stages (requirements, design, coding) by defining risk contexts and factors that can be evaluated before actual testing begins. This preliminary action identifies high-risk areas that require intensive testing, allowing comprehensive defect detection to be focused on critical areas rather than uniformly applied across all components, thus reducing overall time consumption.
Solution Approach 2:
The patent implements a feedback mechanism where risk assessments at one level inform testing strategies at other levels. Test results feed back into risk factor evaluations, which then adjust the testing scope and intensity. This dynamic feedback loop ensures comprehensive defect detection in high-risk areas while minimizing testing effort in low-risk areas, optimizing the balance between detection capability and time consumption.
3Productivity
If risk-based testing is implemented across all software levels, then testing effectiveness is improved, but the complexity of test planning and execution increases
Solution Approach 1:
The patent segments the testing process into distinct levels (unit testing, integration testing, system testing) with specific risk contexts defined for each level. Test planning complexity is managed by focusing on level-specific risk factors rather than attempting to assess all risks at all levels simultaneously. This segmentation improves testing effectiveness by ensuring appropriate test strategies are applied at each level while keeping planning complexity manageable.
Solution Approach 2:
The patent creates a universal risk assessment framework that can be applied across all software development levels and phases. The same basic structure of risk contexts, factors, and scoring mechanisms is used universally, but adapted to specific level requirements. This universality improves testing effectiveness by providing consistent risk-based guidance throughout the development lifecycle while reducing test planning complexity through reuse of the same framework and methodologies.
Data Source
AI summary
A method is implemented in a computer infrastructure having computer executable code tangibly embodied on a computer readable storage medium having programming instructions. The programming instructions are operable to receive one or more risk factors, receive one or more contexts, identify one or more context relationships and associate the one or more contexts with the one or more risk factors. Additionally, the programming instructions are operable to map the one or more risk factors for an associated context to a software defect related risk consequence to determine a risk model and execute a risk-based testing based on the risk model to determine a defect related risk evaluation for a software development project.


