experiments-issta

Experimental Evaluation: Data and Scripts

General Information

This folder contains the data we obtained by conducting the experimental procedure described in the paper (Section 4). We used this data to generate the plots reported in the paper.

Dependencies

The scripts require make and python 3.7

Configure Ubuntu

Pull an Ubuntu Docker image, run and configure it by typing in the terminal:

docker pull ubuntu:bionic
docker run -it --rm ubuntu:bionic
apt-get update && apt-get upgrade -y && apt-get clean
apt-get install make

And check if Make is correctly installed, by typing the following command:

make -version
GNU Make 4.1

Check that the version of Make matches 4.1.

Copy the project into the docker container

To copy DeepHyperion inside the docker container, open another console and run:

docker cp <DEEP_HYPERION_HOME>/ <DOCKER_ID>:/

Where <DEEP_HYPERION_HOME> is the location in which you downloaded the artifact and <DOCKER_ID> is the ID of the ubuntu docker image just started.

You can find the id of the docker image using the following command:

docker ps -a

CONTAINER ID   IMAGE           COMMAND       CREATED          STATUS          PORTS     NAMES
13e590d65e60   ubuntu:bionic   "/bin/bash"   2 minutes ago   Up 2 minutes             recursing_bhabha

Installing Python 3.7

Install Python 3.7:

apt-get install -y curl python3.7 python3.7-dev python3.7-distutils
update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.7 1
update-alternatives --set python3 /usr/bin/python3.7
curl -s https://bootstrap.pypa.io/get-pip.py -o get-pip.py && \
    python3 get-pip.py --force-reinstall && \
    rm get-pip.py
apt-get install -y python3.7-venv

And check if it is correctly installed, by typing the following command:

python3 -V

Python 3.7.5

Check that the version of python matches 3.7.*.

Installing pip

Use the following commands to install pip and upgrade it to the latest version:

apt install -y python3-pip
python3 -m pip install --upgrade pip

Once the installation is complete, verify the installation by checking the pip version:

python3 -m pip --version

pip 21.1.1 from /usr/local/lib/python3.7/dist-packages/pip (python 3.7)

(Re)Generate the plots

To regenerate the plots, run the following command from the current folder:

cd DeepHyperion/experiments
make plot-all

This command sets up a python virtual environment in a predefined location (./.venv), extracts into the data/mnist and data/beamng folders the raw data (feature-maps, probability-maps, etc.), and creates the various plots.

The command checks that the expected version of python is installed and fails otherwise.

The command produces a verbose output (sorry) and a few warnings like the following one:

...
plotting_utils.py:354: RuntimeWarning: Mean of empty slice
  avg_probabilities = np.nanmean(all_probabilities, axis=0)
...

Those warnings are expected, so do not worry.

If everything worked as expected you'll find the following plots under ./plots:

• RQ1-MNIST.pdf (Figure 3: RQ1: Misbehaviours found by DeepHyperion, DeepJanus and DLFuzz on MNIST)
• RQ1-BeamNG.pdf (Figure 4: RQ1: Misbehaviours found by DeepHyperion and DeepJanus on BeamNG)
• RQ2-MNIST.pdf (Figure 5: RQ2: Map cells filled by DeepHyperion, DeepJanus and DLFuzz on MNIST)
• RQ2-BeamNG.pdf (Figure 6: RQ2: Map cells filled by DeepHyperion and DeepJanus on BeamNG)
• RQ3-MNIST.pdf (Figure 7: RQ3: Probability maps and feature discrimination for MNIST)
• RQ3-BeamNG.pdf (Figure 8: RQ3: Probability maps and feature discrimination for BeamNG)

Those plots corresponds to the ones reported in Figures 3 -- 8 of the (pre-print) version of the paper.