Abstract
Model-based testing of single functions is usually based on logical properties as specification. In practice it appears to be rather hard to develop a sufficiently strong set of properties to spot all errors. For model-based testing of state based systems one usually employs a state machine as model and a conformance relation between this specification and the software under test. For (abstract) data types we can use both ways of model-based testing. In this paper we compare the specification effort required to make a model that is able to find issues and the number of tests needed to find issues for some well-known data types. Our examples show that it can be easier to write state based specifications. Moreover, state based testing of data types finds more implementation issues and is very efficient.
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Koopman, P., Achten, P., Plasmeijer, R. (2012). Model Based Testing with Logical Properties versus State Machines. In: Gill, A., Hage, J. (eds) Implementation and Application of Functional Languages. IFL 2011. Lecture Notes in Computer Science, vol 7257. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34407-7_8
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