Meta-model for automated risk-based testing

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Solution Overview

Problem

Manual risk-based testing is complex, time-consuming, and error-prone, lacking a digital format for combining risk-based testing within a computer system, leading to inconsistencies and inefficiencies.

Innovation Solution

A computer-implemented method using a meta-model stored in a computer-readable storage medium, comprising risk, test, and objective elements with associated parameters, allowing for efficient and reliable risk-based testing by calculating test priority numbers and exposure parameters, and storing instances for automated processing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If manual risk-based testing is used, then flexibility in risk assessment is maintained, but complexity and time consumption increase significantly

Engineering Contradiction:

Improveflexibility in risk assessmentVSAvoidcomplexity of testing process

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The patent replaces the manual mechanical process of risk assessment with an automated computer-based system. The meta-model and processing device automatically calculate risk priorities, test effectiveness scores, and generate test cases, substituting human manual operations with computational processes that reduce complexity while maintaining assessment flexibility.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service automated testing where the processing device autonomously executes risk-based testing without requiring manual intervention at each step. The meta-model automatically prioritizes test cases and manages the testing process, allowing the system to serve itself and reducing the operational burden on testers.

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If manual risk-based testing is used, then adaptability to different risk scenarios is maintained, but time consumption increases

Engineering Contradiction:

Improveadaptability to different risk scenariosVSAvoidtime consumption for testing

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The patent uses parameter changes to adapt the testing process to different risk scenarios. The meta-model allows dynamic adjustment of risk parameters, probability values, and consequence weights based on specific testing scenarios. This enables the system to quickly adapt to different risk situations by modifying numerical parameters rather than restructuring the entire testing approach, significantly reducing time consumption.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If manual maintenance of risk lists is used, then human judgment is applied, but errors and inconsistencies increase

Engineering Contradiction:

Improveaccuracy of risk assessmentVSAvoidcomplexity of manual processes

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent replaces manual human judgment processes with automated computational algorithms. The processing device systematically applies the meta-model to calculate risk priorities and test effectiveness, eliminating human errors and inconsistencies while maintaining the complexity management through structured automated processes.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Reliability

If comprehensive testing is performed, then coverage is improved, but resource efficiency decreases

Engineering Contradiction:

Improvetesting coverageVSAvoidresource efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent segments the testing process into prioritized groups based on risk levels. The meta-model divides test cases into high-priority, medium-priority, and low-priority segments, allowing comprehensive testing coverage to be achieved systematically. Resources are allocated efficiently by focusing first on high-priority segments that cover the most critical risks, then progressively addressing lower-priority segments as resources become available.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system uses parameter changes to dynamically adjust testing scope and resource allocation. By calculating risk priority parameters and test effectiveness scores, the system can adaptively determine the optimal level of testing for different system components, achieving comprehensive coverage where needed while reducing testing intensity in lower-risk areas, thereby improving overall resource efficiency.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS11416363B2Method for risk-based testing

Publication Date: 2022.08.16 SIEMENS AG

AI summary

Provided is a computer-implemented method, the method including storing a meta-model in a computer-readable storage medium, wherein the meta-model includes at least one risk element, at least one test element and at least one objective element, and associations between the elements, wherein each risk element is associated with one or more objective elements, and/or each risk element is associated with one or more test elements, wherein at least one element of the elements and/or at least one association has at least one associated risk-related parameter. A corresponding computer program product and system is also provided.