This Master's Thesis describes one example on how to automatically generate tests for real-time protocol software. Automatic test generation is performed using model-based testing (MBT). In model-based testing, test cases are generated from the behaviour model of the system under test (SUT). This model expresses the requirements of the SUT. Many parameters can be varied and test sequences randomised.
In this context, real-time protocol software means a system component of Nokia Siemens Networks (NSN) Long Term Evolution (LTE) base station. This component, named MAC DATA, is the system under test (SUT) in this study. 3GPP has standardised the protocol stack for the LTE eNodeB base station. MAC DATA implements most of the functionality of the Medium Access Control (MAC) and Radio Link Control (RLC) protocols, which are two protocols of the LTE eNodeB.
Because complex telecommunication software is discussed here, it is challenging to implement MBT for the MAC DATA system component testing. First, the expected behaviour of a system component has to be modelled. Because it is not smart to model everything, the most relevant system component parts that need to be tested have to be discovered. Also, the most important parameters have to be defined from the huge parameter space. These parameters have to be varied and randomised. With MBT, a vast number of different kind of users can be created, which is not reasonable in manual test design. Generating a very long test case takes only a short computing time.
In addition to functional testing, MBT is used in performance and worst-case testing by executing a long test case based on traffic models. MBT has been noticed to be suitable for challenging performance and worst-case testing. This study uses three traffic models: smartphone-dominant, laptop-dominant and mixed. MBT is integrated into continuous integration (CI) system, which automatically runs MBT test case generations and executions overnight. The main advantage of the MBT implementation is the possibility to create different kinds of users and simulate real-life system behaviour. This way, hidden defects can be found from test environment and SUT.
