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With AltWalker, automation code related to our model can be implemented in Python, C#, or other. In this approach, GraphWalker is only responsible for generating the path through the models.
Starting by clarifing clarifying some key concepts, using the information provided by GraphWalker's documentation that explains them clearly:
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From a model, GraphWalker will generate a path through it. A model has a start element, and a generator which rules how the path is generated, and an associated stop condition which tells GraphWalker when to stop generating the path.
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In MBT, especially in the case of State Transition Model-Based Testing, we start from a given vertex but then the path, that describes the sequence of edges and vertices visited, can be quite different each time the tool generates it. Besides, the stop condition is not composed by of one or more well-known and fixed expectations; it's based on some more graph/model related criteria.
When we "execute the model", it will walk the path (i.e. go over from vertex to vertex through a given edge) and performing checks in the vertices. If those checks are successful until the stop condition(s) is achiviedachieved, we can say that it was successful; otherwise, the model is not a good representation of the system as it is and we can say that it "failed".
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In this tutorial, is based on the example provided by the GraphWalker community (please check GraphWalker wiki page describing it) which targets the well-known PetClinic sample site.
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