The wide-scale introduction of model-based testing techniques in an industrial context faces many obstacles. One of the obstacles is the existing methodology gap between informally described test purposes and formally defined test descriptions used as the starting point for test automation. The provision of an explicit test description becomes increasingly essential when integrating complex, distributed systems and providing support for conformance and interoperability tests of such systems. The upcoming ETSI standard on the Test Definition Language (TDL) covers this gap. It allows describing scenarios on a higher abstraction level than programming or scripting languages. Furthermore, TDL can be used as an intermediate representation of tests generated from other sources, e.g. simulators, test case generators, or logs from previous test runs. TDL is based on a meta-modelling approach that expresses its abstract syntax. Deploying this design approach, individual concrete syntaxes of TDL can be designed for different application domains. The paper provides an overview of TDL and discusses its application on a use case from the rail domain.

We describe a model-based construction of an online tester for black-box testing of the implementation under test(IUT). The external behaviour of the IUT is modelled as an output observable nondeterministic EFSM with the assumption that all transition paths are feasible. A test purpose is attributed to the IUT model by a set of Boolean variables called traps that are used to measure the progress of the test run. These variables are associated with the transitions of the IUT model. The situation where all traps have been reached means that the test purpose has been achieved. We present a way to construct a tester that at runtime selects a suboptimal test path from trap to trap by finding the shortest path to the next unvisited trap. The principles of reactive planning are implemented in the form of the decision rules of selecting the shortest paths at runtime. The decision rules are constructed in advance from the IUT model and the test purpose. Preliminary experimental results confirm that this method clearly out performs random choice and is better than the anti-ant algorithm in terms of resultant test sequence length to achieve the test purpose