aNNoTest
aNNoTest is a tool (and an approach) to automatically generating bug-finding inputs for NN program testing. Paper An annotation-based approach for finding bugs in neural network programs by Mohammad Rezaalipour and Carlo A. Furia explains aNNoTest in details and provides guidelines on how to use it, effectively.
Installation
aNNoTest can be installed in two ways. To install it from PyPi, use the following command.
pip install annotest
It can also be installed from source code:
git clone git@github.com:atom-sw/annotest.git
cd annotest
pip install .
We have tested aNNoTest on Python 3.6. But it should work on Python 3.6+ as well.
Using aNNoTest
aNNoTest is a command line tool.
After annotating your project with
aN (aNNoTest's annotation language)
you can cd to your project directory
and then run aNNoTest.
cd path_to_python_project
annotest
Or you can input the project path to aNNoTest when running it:
annotest path_to_python_project
Examples
To see examples of using aNNoTest, see the following repository:
https://github.com/atom-sw/annotest-subjects
Citations
@article{Rezaalipour:2023,
title = {An annotation-based approach for finding bugs in neural network programs},
journal = {Journal of Systems and Software},
volume = {201},
pages = {111669},
year = {2023},
issn = {0164-1212},
doi = {https://doi.org/10.1016/j.jss.2023.111669},
url = {https://www.sciencedirect.com/science/article/pii/S016412122300064X},
author = {Mohammad Rezaalipour and Carlo A. Furia},
keywords = {Test generation, Neural networks, Debugging, Python}
}
Mirrors
The current repository is a public mirror of our internal private repository. We have two public mirrors, which are as follows:
