BART
The Behavioural Analysis and Regression Toolkit is based on TRAPpy. The primary goal is to assert behaviours using the FTrace output from the kernel.
Target Audience
The framework is designed to cater to a wide range of audience. Aiding developers as well as automating the testing of "difficult to test" behaviours.
Kernel Developers
Making sure that the code that you are writing is doing the right thing.
Performance Engineers
Plotting/Asserting performance behaviours between different revisions of the kernel.
Quality Assurance/Release Engineers
Verifying behaviours when different components/patches are integrated.
Installation
The following instructions are for Ubuntu 14.04 LTS but they should also work with Debian jessie. Older versions of Ubuntu or Debian (e.g. Ubuntu 12.04 or Debian wheezy) will likely require to install more packages from pip as the ones present in Ubuntu 12.04 or Debian wheezy will probably be too old.
Required dependencies
Install additional tools required for some tests and functionalities
$ sudo apt install trace-cmd kernelshark
Install the Python package manager
$ sudo apt install python-pip python-dev
Install required python packages
$ sudo apt install libfreetype6-dev libpng12-dev python-nose
$ sudo pip install numpy matplotlib pandas ipython[all]
$ sudo pip install --upgrade trappy
ipython[all]
will install IPython
Notebook, a web based interactive
python programming interface. It is required if you plan to use interactive
plotting in BART.
Install BART
$ sudo pip install --upgrade bart-py
For developers
Instead of installing TRAPpy and BART using pip
you should clone the repositories:
$ git clone git@github.com:ARM-software/bart.git
$ git clone git@github.com:ARM-software/trappy.git
Add the directories to your PYTHONPATH
$ export PYTHONPATH=$BASE_DIR/bart:$BASE_DIR/trappy:$PYTHONPATH
Trace Analysis Language
BART also provides a generic Trace Analysis Language, which allows the user to construct complex relation statements on trace data and assert their expected behaviours. The usage of the Analyzer module can be seen for the thermal behaviours here
Scheduler Assertions
Enables assertion and the calculation of the following parameters:
Runtime
The total time that the task spent on a CPU executing.
Switch
Assert that a task switched between CPUs/Clusters in a given window of time.
Duty Cycle
The ratio of the execution time to the total time.
Period
The average difference between two switch-in or two switch-out events of a task.
First CPU
The first CPU that a task ran on.
Residency
Calculate and assert the total residency of a task on a CPU or cluster.
Examples
The Scheduler assertions also use TRAPpy's EventPlot to provide a kernelshark
like timeline for the tasks under consideration. (in IPython notebooks).
A notebook explaining the usage of the framework for asserting the deadline scheduler behaviours can be seen here.
API reference
The API reference can be found in https://pythonhosted.org/bart-py