Extending behavioral test models with symbolic data
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Abstract
Model-based testing is a technique to automatically generate test cases and oracles in order to test an implementation. A typical behavrial model used for model-based testing is a Labeled Transition System9LTS). However cre-ating the LTS models needed for testing is a complex task, and especially when data is involved the number of states and thus the complexity will explode fast. Incorporating data in an LTS leads to a Symbolic Transitions System (STS), where data is stored in variables and actions have guards and updates. The result is that the number of states is reduced and the complexity is moved to the update rules and guards. In order to simplify the construction of STS an algorithm is presented that is capable of extracting data form an implementation and enriching the LTS model in order to from an STS. A domain expert can than inspect the model for possible faults and in the future the model can be used for regression testing of the implementation.