Test Case Relevance Ranking Using Optimal Control Constraints
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Solution Overview
Problem
Existing methods for testing technical systems are inefficient and costly, as they require exhaustive testing of all scenarios without prioritization, leading to significant resources being wasted if a single test case fails.
Innovation Solution
A method to rate the relevance of test cases by minimizing a scalar dynamics function and its integral, using optimized control problems, allowing selective prioritization of critical test cases based on their proximity to an optimal solution, enabling rapid and cost-effective testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If exhaustive testing of all test cases is performed, then the reliability of the technical system is improved, but the loss of time and resources increases significantly
Solution Approach 1:
The patent applies preliminary action by calculating the relevance of each test case before actual execution. The relevance is determined by computing the probability that the technical system behaves as expected, based on the scalar dynamics function and integral. Test cases are pre-sorted by relevance, allowing the most critical tests to be executed first, thereby avoiding exhaustive testing while maintaining high reliability assessment.
Solution Approach 2:
The patent changes the parameter of test case selection from uniform/random to relevance-based prioritization. By introducing the relevance parameter calculated from the scalar dynamics function L(x,u,t) and its integral, the system dynamically determines which test cases are most important, transforming the testing approach from exhaustive to selective based on computed relevance values.
2Reliability
If all test cases are tested without prioritization, then the completeness of testing is improved, but the loss of resources increases
Solution Approach 1:
The patent performs preliminary calculation of test case relevance before execution. The relevance is computed using the scalar dynamics function and integral for each test case, creating a prioritized list in advance. This allows resources to be allocated efficiently by first executing high-relevance test cases, reducing the total number of tests needed while maintaining comprehensive coverage of critical system behaviors.
Solution Approach 2:
The patent introduces the relevance parameter as a filtering criterion for test case selection. Instead of treating all test cases equally, the system uses the relevance value (derived from the scalar dynamics function) to determine which test cases warrant full execution, thereby optimizing resource allocation while maintaining testing completeness for critical scenarios.
3Ease of operation
If test cases are executed in arbitrary order, then the simplicity of the testing process is improved, but the productivity of testing is reduced
Solution Approach 1:
The patent applies preliminary action by pre-calculating and sorting test cases based on relevance before execution begins. The test cases are arranged in descending order of relevance, creating an optimized execution sequence. This maintains operational simplicity through automated relevance calculation while significantly improving productivity by executing the most critical tests first, reducing the total testing time required.
Solution Approach 2:
The patent changes the execution order parameter from arbitrary to relevance-based prioritization. By computing the relevance value for each test case using the scalar dynamics function and integral, the system dynamically determines the optimal execution sequence, transforming the testing process from simple but inefficient to structured and highly efficient.
Data Source
AI summary
A method for rating the relevance of a test case for assessing the behavior of a technical system, whose dynamics are described by a scalar dynamics function in the current state of the system, in the control currently impressed upon the system, as well as in the time. In the method: an optimized control problem is set up, in which the scalar dynamics function and/or an integral thereof with respect to time, is to be minimized under the boundary condition that the dynamics of the technical system in the first order is limited to a function; it is ascertained how closely the test case approaches a solution of the optimized control problem; and the closer the test case approaches a solution of the optimized control problem, the more relevant the test case is rated for the assessment of the behavior of the technical system.