Abstract: A computer-implemented method for comparing generated data sequences for an at least semi-automated driving of a mobile platform, which were generated with the aid of a closed-loop simulation process, and a recorded data sequence of a trip of the mobile platform, controlled in at least semi-automated fashion, for the qualification of the control. The method includes: providing the recorded data sequence, which is based on a multiplicity of determinants, of trips of the mobile platform controlled in at least semi-automated fashion; providing a multitude of generated data sequences, which are based on the multiplicity of determinants, of simulated trips, which were generated with the aid of the closed-loop simulation process; providing similarity limits and a similarity metric for the respective determinant; comparing the recorded data sequence to each individual generated data sequence of the multitude of recorded data sequences.

Abstract: A method for testing a technical system. 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 different error measures of the simulation. On the basis of the fulfillment measure and each of the error measures, a classification of the tests is carried out as either reliable or unreliable case by case. A selection among the error measures is made on the basis of a number of the tests classified as reliable.

Abstract: A computer-implemented method for testing a product, in particular software, hardware, or a system comprising hardware and software, in which, depending on input parameters, a simulation of the product is carried out, with the aid of which a particular property of the product is tested. Depending on a comparison between a result of the simulation and a requirement made of the particular property, a first classification is output for the result of the simulation. Depending on a comparison between reference data from an alternative test of the particular property of the product and the requirement made of the particular property, a second classification is determined. Depending on the first classification and the second classification, an accuracy or robustness of the simulation is determined.

Abstract: A method for evaluating a simulation model. In the method, for selected test cases, a first performance index is calculated in the simulation model. For the same test case, a second performance index is ascertained in a real test environment. For each of the test cases, a difference is calculated between the first performance index and the second performance index, and a signal metric is determined. For each of the signal metrics, an interrelation between the difference and the respective signal metric is investigated. The signal metric that exhibits the closest interrelation with the difference is selected.

Abstract: 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.

Abstract: 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, and a test database is improved on the basis of the classification.

Abstract: A method for testing a technical system. 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 different error measures of the simulation. On the basis of the fulfillment measure and each of the error measures, a classification of the tests is carried out as either reliable or unreliable case by case. A selection among the error measures is made on the basis of a number of the tests classified as reliable.

Abstract: 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, and a test database is improved on the basis of the classification.

Abstract: 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.

Abstract: A method for optimizing test cases. The method includes the following features. On the basis of simulation data obtained by way of the simulation, a simulation metamodel is created. On the basis of measurements performed in the test environment, a reality metamodel is created. Uncertainties inherent in the simulation data and measurements are combined by the fact that either the sum is calculated or the worst case of the two calculations is used or the worst case is respectively considered for each uncertainty being considered. On the basis of the combination of the uncertainties, a metamodel encompassing the simulation and the test environment is created. A search-based optimization of the test cases is performed by way of the metamodel.

Abstract: A method for evaluating a simulation model. In the method, for selected test cases, a first performance index is calculated in the simulation model. For the same test case, a second performance index is ascertained in a real test environment. For each of the test cases, a difference is calculated between the first performance index and the second performance index, and a signal metric is determined. For each of the signal metrics, an interrelation between the difference and the respective signal metric is investigated. The signal metric that exhibits the closest interrelation with the difference is selected.