What methods exist for testing computer models?

Several methods exist for testing computer models, including unit testing, integration testing, system testing, and acceptance testing.

Unit testing is the first level of testing and involves testing individual components or units of a software application. This method is typically performed by the developers themselves. The main purpose of unit testing is to validate that each unit of the software performs as designed. A unit is the smallest testable part of any software, often a program module or an object, and it usually has one or a few inputs and usually a single output.

Integration testing is the next level of testing, which involves combining and testing individual units as a group. This method is used to expose faults in the interaction between integrated units. There are different approaches to integration testing, such as top-down, bottom-up, and sandwich (a combination of top-down and bottom-up), each with its own advantages and disadvantages.

System testing, on the other hand, is a high level of testing that validates the complete and fully integrated software product. The purpose of this testing is to evaluate the system’s compliance with the specified requirements. It's usually performed by a team that is independent of the development team, so as to provide an unbiased view of the software.

Lastly, acceptance testing is performed after system testing and before making the system available for actual use. This type of testing is done to ensure that the system meets the requirements specified in the system requirements specification (SRS) document. It's usually performed by the client or end users, and not by the developers.

In addition to these, there are other testing methods such as regression testing, which is done to confirm that a recent program or code change has not adversely affected existing features, and performance testing, which is done to determine the system performance under varying loads. Each of these methods plays a crucial role in ensuring the reliability and robustness of computer models.