Virtual Test Classifier for Embedded System Simulation Reliability
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Solution Overview
Problem
Current model-based testing methods for embedded systems lack reliability, leading to limited trust in simulation results, which hinders their incorporation into release decisions, especially in critical areas like automotive engineering and robotics.
Innovation Solution
A virtual test classifier is introduced to assess the reliability of simulation results by combining signal metrics and quantitative specifications, enabling a binary decision on whether virtual tests are trustworthy, thereby reducing the need for real system tests and improving testing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If model-based testing is used to automate test activities and generate test artifacts, then productivity is improved, but reliability deteriorates due to lack of trust in simulation results
Solution Approach 1:
The patent implements a feedback mechanism by comparing simulation results with real measurement data from the system under test. The virtual test classifier uses this comparison to assess simulation quality and generate feedback that improves the reliability assessment of model-based testing results, thereby maintaining productivity while enhancing trust in simulation outcomes
Solution Approach 2:
The patent replaces physical testing mechanisms with a virtual testing system that uses signal metrics and machine learning-based quality assessment. This substitution allows automated test execution with reliability evaluation, maintaining high productivity while establishing trust through systematic comparison with real system behavior
2Loss of time
If the number of real system tests is reduced using virtual tests, then loss of time is improved, but reliability deteriorates due to uncertain simulation accuracy
Solution Approach 1:
The patent substitutes physical system testing with virtual testing using simulation models. The virtual test classifier assesses simulation quality by comparing with limited real measurement data, enabling time-efficient testing while maintaining reliability through systematic quality assessment of the virtual test results
Solution Approach 2:
The patent changes the testing approach by introducing parameter-based quality assessment using signal metrics (amplitude, frequency, phase). This allows the system to evaluate simulation accuracy for different test scenarios and adjust the reliance on virtual tests accordingly, reducing testing time while maintaining reliability through parameter-driven quality control
3Device complexity
If simulation models are used for testing embedded systems, then device complexity is reduced, but measurement precision deteriorates due to inability to accurately predict real system behavior
Solution Approach 1:
The patent replaces complex physical testing setups with a virtual testing system that uses signal metrics and machine learning. This substitution reduces device complexity while improving measurement precision through systematic comparison of simulation results with real system behavior across multiple signal dimensions
Solution Approach 2:
The virtual test classifier serves multiple functions: it assesses simulation quality, predicts real system behavior accuracy, and guides test execution decisions. This multi-functionality reduces the need for separate testing systems while improving measurement precision through integrated analysis of signal metrics and simulation quality
Data Source
AI summary
A method for testing a technical system. The method includes: tests are carried out with the aid of a simulation of the system, the tests are evaluated with respect to a fulfillment measure of a quantitative requirement on the system and an error measure of the simulation, on the basis of the fulfillment measure and error measure, a classification of the tests as either reliable or unreliable is carried out.