Model-based testing in Python
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README.md

PyModel: Model-based testing in Python

PyModel is an open-source model-based testing framework in Python.

In model-based testing, you code a model that can generate as many test cases as needed. The model also checks the test outcomes. Model-based testing is helpful where so many test cases are needed that it is not feasible to code them all by hand.

In the samples included with PyModel, there are models and test scripts for network sockets, a communication protocol, embedded controllers, some data structures, a multithreaded application, and a web application.

PyModel includes an analyzer for validating models, visualizing their behavior, and checking their safety properties.

PyModel can generate offline tests which are similar to unit tests, but the typical way to use PyModel is on-the-fly testing, where the test runner uses the model to compute the test run as it executes, so test runs can be as long as needed. On-the-fly testing can cope with nondeterminism and asynchrony in the system under test.

PyModel can combine models using composition, guide tests through programmed scenarios, and focus test coverage according to programmed strategies.

PyModel provides three main programs:

  • pma, PyModel analyzer: generates a finite state machine (FSM) and computes properties by exploring a model program, FSM, test suite, or a product of these.

  • pmg, PyModel graphics: generates a file of graphic commands from an FSM, that can be processed by the Graphviz dot command to produce graphics files in various formats including svg, pdf, and ps.

  • pmt, PyModel tester: displays traces, generates tests offline, executes offline tests, or generates and executes tests on-the-fly.

There is also a fourth program:

  • pmv, PyModel viewer: invokes pma, pmg, and the Graphiz dot command (to display the graphics generated by pmg). The pmv program provides brevity and convenience, so analysis and display can be accomplished by a single command.

Use pma and pmg (or pmv) to visualize and preview the behavior of pmt. Every path through the graph created by pma (and drawn by pmg) is a trace (test run) that may be generated by pmt, when pma and pmt are invoked with the same arguments. The pma program is also useful on its own for visualization and safety analysis.

For more information, read the notes, browse the code, peruse the talks, or try the samples. There are README files in most of the directories. The most thoroughly explained sample is Socket, which demonstrates several PyModel techniques for modeling and testing systems that exhibit nondeterminism, concurrency, and asynchrony.

Here are the slides for talks on PyModel given at NWPD10 and SciPy 2011. Here is the paper from the SciPy 2011 Proceedings.

You can INSTALL PyModel.

PyModel is also available at PyPI and at the author's web page.

PyModel requires Python 2.6 or higher (because it uses itertools.product)

PyModel is influenced by NModel, but is not a translation or re-implementation.

PyModel is covered by the BSD License

Code and documents are copyright (C) 2009-2013, Jonathan Jacky.

Revised May 2013