The Automated Test System

Purpose and Features

The Automated Testing System (ATS) is an open-source, Python-based tool for automating the running of tests of an application. ATS can test any program that can signal success or failure via its exit status.

ATS is distributed, introspective, and scalable.

  • It is distributed in two senses. First, there is no central database of tests to run. Tests may be spread over many directories and usually adding a test in a subdirectory is entirely a local operation.

  • Introspective means that a test can be runnable by someone who is not an expert, yet runnable with different arguments by someone who is. An application test may contain within itself, in comments, directions for how to run itself in one or more ways. An expert may run these tests normally using his application; but when ATS runs it, it runs the application according to the special comments within the input.

  • Depending on the available resources, the execution of the tests can be done over many processors and hosts, in parallel. Distributed execution and test specification helps ATS stay scalable.

Other features of ATS include:

  • A test may depend on another test, and will not be executed unless their parent test succeeds.

  • Tests may be filtered out (that is, not executed) in many ways. These may include number of processors, time limit, platform, or other user-defined criteria.

  • A level may be given to each test, and used to stratify a test suite into subsets of increasing thoroughness.

  • ATS is extensible. The ats driver script does almost nothing except import the ats module and call the ats.manager.main() method. It may suit your purposes to make a different driver that does things before or after this invocation. The ats script uses the assets of the module ats to provide a command line interface-type testing system. Other interfaces, such as a GUI interface, are possible.

  • ATS makes it easy in particular to postprocess the results of the testing by registering routines to be executed after the tests have completed, but before exiting.

  • A facility is provided to make it easy to port ATS to new machines such as parallel processors and multi-noded distributed machines, or to take advantage of multiple cores. The ‘stock’ ATS will run up to two tests at once, each of them standard serial jobs (np = 1 in what follows).

While ATS input can be written using the full power of Python, the basic operations require only a few statements written in a special vocabulary that is not be hard to learn. For example:

     clas="-input mydeck delta=3",

executes the given executable with the given command-line arguments (clas), launching the job is parallel on 3 processors.


A note on function signatures While this document assumes you can learn the basics of Python on your own, function signatures require careful understanding. In Python, the definition of a function parameter can have one or two asterisks in front of a name.

  • When calling such a function, in the place of a parameter with one asterisk in front of it, you can give zero or more comma-separated values as a value, which the function will receive as a list.

  • When a parameter name has two asterisks in front of it in the function definition, you can give zero or more comma-separated keyword = value pairs when you call it, which the function will receive as a dictionary.

For example, the ATS source function has the signature:

source(*paths, **vocabulary)

which means any of the following are legitimate calls to it:

source('', '')
source('', physics="on", music = "off")
source(physics="on", music = "off")

As it happens, the last of these doesn’t do anything, but it is a legitimate call.


All of the paths arguments must come before the first of the vocabulary arguments.

Download and Install

Installation of ATS is easy. Unpack the distribution and in the top-level directory execute:

python install

Public releases are at

The README.txt file contains installation instructions. ATS has been tested with Python 2.6 or later, available at

ATS should translate to Python 3 by using the 2to3 utility but this has not yet been tried.

ATS should work, or be made to work, on any system which can run Python via a command window. In particular it works out of the box on any Linux or Mac system. ATS works on Windows but experience there is limited.


ATS was written by Paul F. Dubois at Lawrence Livermore National Laboratory, (LLNL) in about 2003. Although an open-source release was made, the software was highly oriented to the LLNL computer systems and one particular simulation, ATS has been in continuous use since then.

A revision in 2010-11 has compartmentalized the LLNL-specific system details, and we have added new features to make the software more generally applicable and more easily portable.

The support team at LLNL includes Nu Ai Tang, T. J. Alumbaugh, and Ines Heinz. You can contact the author at For help with the LLNL features contact

ATS was written to test scientific simulations, although it can be used for any program that can be run with a command-line, does not require interaction, and which can signal its own success or failure via its exit status (or be executed via a shell program with those properties).

In general scientific programs do not produce predictable printed output, and so comparison of output files, so common in the testing literature, is not normally useful.They also are generally long-running and resource-consuming; hence ATS emphasises filtering, parallel execution, and prioritization under user control. Provision for supporting batch execution is also provided.

LLNL Notes

The LC distribution includes an LC directory containing definitions for the local machines and the batch system. To make use of the features of LC machines you will need to set either SYS_TYPE or MACHINE_TYPE. To install the LC machines, run:

python install

in the LC directory after you have done so in the main ATS directory.

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About The Documentation

This document is licensed under the terms of the LICENSE.txt file in the ATS distribution.

This documentation is written in reStructuredText, the standard language used by the Python documentation project. You should find the source, available in the distribution, readable even without rendering. It can be if desired rendered into plain text files, web pages, PDF files, and other formats using the tools of the Sphinx project. The source files are located in the source subdirectory of the docs directory. The Makefile in the docs directory will render the documents into the build subdirectory if appropriate parts of Sphinx have been installed.

If you install setuptools into your Python, you can get Sphinx with:

easy_install -U Sphinx