Test Scenario Prioritization via Risk and Criticality Weights
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Solution Overview
Problem
Existing software testing methods generate a large volume of test cases, making it inefficient to achieve maximum coverage and quality, as they do not effectively manage the number of test scenarios.
Innovation Solution
A method and system that create a test process model with interaction paths, determine risk and criticality weights for each test scenario, and identify critical scenarios based on these weights, to generate a manageable set of integrated test scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all possible test scenarios are generated based on combination of various processes, then test coverage is improved, but the volume of test cases becomes unmanageably large
Solution Approach 1:
The patent extracts only the critical test scenarios from the complete set of possible test scenarios by applying risk weight and criticality weight filters. This selective extraction maintains adequate test coverage while dramatically reducing the volume of test cases that need to be executed, resolving the contradiction between comprehensive coverage and manageable test case volume.
Solution Approach 2:
The patent changes the parameters of test scenario selection by introducing risk weight and criticality weight as filtering criteria. By adjusting these weight parameters, the system can dynamically control which test scenarios are selected for execution, enabling optimization of the balance between test coverage and test case volume based on specific project requirements.
2Reliability
If a large volume of test cases is designed and executed, then test coverage is improved, but testing efficiency deteriorates
Solution Approach 1:
The patent extracts only the essential test scenarios that provide maximum coverage value by applying risk and criticality weight filters. This extraction eliminates redundant test cases, thereby maintaining adequate coverage while significantly improving testing efficiency by reducing the time and resources required to execute the test suite.
Solution Approach 2:
The patent applies partial action by selecting only a subset of test scenarios that are most critical based on risk and criticality weights, rather than executing all possible test cases. This partial execution approach achieves sufficient test coverage with improved efficiency, avoiding the waste of resources on less critical test scenarios.
3Ease of operation
If risk weight and criticality weight calculations are performed for each test scenario, then test scenario prioritization is improved, but processing complexity increases
Solution Approach 1:
The patent implements self-service by automatically calculating risk weights and criticality weights for test scenarios using predefined criteria and algorithms. The system autonomously performs the prioritization analysis without requiring manual intervention, thereby improving ease of operation while the automated nature of the process keeps processing complexity manageable through systematic computation.
Data Source
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AI summary
This disclosure relates to generating integrates test scenarios. The method includes creating a test process model comprising a plurality of processes and one or more interaction paths amongst the plurality of processes based on process information; identifying a plurality of test scenarios based on an analysis of the plurality of processes and the one or more interaction paths amongst the plurality of processes, wherein each of the plurality of test scenarios comprises a unique process flow path; determining a risk weight and a criticality weight associated with each of the plurality of test scenarios; and identifying at least one test scenario from the plurality of test scenarios based on a comparison of the risk weight and the criticality weight determined for each of the plurality of test scenarios with an associated threshold weight.