Objective testing is mainly used in systems where the data can be recorded while the simulation is running. This testing technique relies on the application of statistical and automated methods to the data collected.
Statistical methods are used to provide an insight into the accuracy of the simulation. These methods include hypothesis testing, data plots, principle component analysis and cluster analysis.
Automated testing requires a knowledge base of valid outcomes for various runs of simulation. This knowledge base is created by domain experts of the simulation system being tested. The data collected in various test runs is compared against this knowledge base to automatically validate the system under test. An advantage of this kind of testing is that the system can continually be regression tested as it is being developed.
Statistical methods are used to provide an insight into the accuracy of the simulation. These methods include hypothesis testing, data plots, principle component analysis and cluster analysis.
Automated testing requires a knowledge base of valid outcomes for various runs of simulation. This knowledge base is created by domain experts of the simulation system being tested. The data collected in various test runs is compared against this knowledge base to automatically validate the system under test. An advantage of this kind of testing is that the system can continually be regression tested as it is being developed.
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