Conference site ยป Proceedings

PyModel: Model-based testing in Python

Jonathan Jacky
University of Washington

Abstract

In unit testing, the programmer codes the test cases, and also codes assertions that check whether each test case passed. In model-based testing, the programmer codes a \textquotedbl{}model\textquotedbl{} that generates as many test cases as desired and also acts as the oracle that checks the cases. Model-based testing is recommended where so many test cases are needed that it is not feasible to code them all by hand. This need arises when testing behaviors that exhibit history-dependence and nondeterminism, so that many variations (data values, interleavings, etc.) should be tested for each scenario (or use case). Examples include communication protocols, web applications, control systems, and user interfaces. PyModel is a model-based testing framework in Python. PyModel supports on-the-fly testing, which can generate indefinitely long nonrepeating tests as the test run executes. PyModel can focus test cases on scenarios of interest by composition, a versatile technique that combines models by synchronizing shared actions and interleaving unshared actions. PyModel can guide test coverage according to programmable strategies coded by the programmer.

Keywords

testing, model-based testing, automated testing, executable specification, finite state machine, nondeterminism, exploration, offline testing, on-the-fly testing, scenario, composition

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