FAVD: Featherweight Assisted Vulnerability Discovery

This repository contains the replication package for the paper "Featherweight Assisted Vulnerability Discovery", David Binkley, Leon Moonen, Sibren Isaacman, Information and Software Technology, 2022, 106844, ISSN 0950-5849, DOI: 10.1016/j.infsof.2022.106844. https://www.sciencedirect.com/science/article/pii/S0950584922000209.

The replication package is archived on Zenodo with DOI: 10.5281/zenodo.5957264. The source code is distributed under the MIT license, the data is distributed under the CC BY 4.0 license.

Repository Organization

The overall process consists of three steps, organized as three directories:

gathering of the labeled function names that are used as the source for step 2, in names
dangerous word identification, in dangerous-words
analysis of the data gathered during step 2, in analysis

The directory Model holds a copy of the pre-trained LAVDNN model as provided by the authors at https://github.com/StablelJay/LAVDNN/raw/master/Model/model_of_LAVDNN

Requirements

The following tools are required for the replication:

python >= 3.5
R
tcsh
csvcut from csvkit
cntk as keras backend for running the LAVDNN model

In addition, the following python packages are needed

Finally, for the analysis in step 3, the following R libraries are needed:

agricolae, ggplot2, reshape2, xtable

Citation

If you build on this data or code, please cite this work by referring to the paper:

@article{binkley2022:featherweight,
   title = {Featherweight assisted vulnerability discovery},
   author = {David Binkley and Leon Moonen and Sibren Isaacman},
   journal = {Information and Software Technology},
   pages = {106844},
   year = {2022},
   issn = {0950-5849},
   doi = {https://doi.org/10.1016/j.infsof.2022.106844},
   url = {https://www.sciencedirect.com/science/article/pii/S0950584922000209},
   copyright = {Open Access},
   publisher = {Elsevier},
}

Acknowledgement

Part of this work has been financially supported by the Research Council of Norway through the secureIT project (RCN contract #288787).

Bumps numpy from 1.21 to 1.22.0.

Release notes

Sourced from numpy's releases.

v1.22.0

NumPy 1.22.0 Release Notes

NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.

A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.

NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.

New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.

A new configurable allocator for use by downstream projects.

These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

Expired deprecations

Deprecated numeric style dtype strings have been removed

Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

(gh-19539)

Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

(gh-19615)

... (truncated)

Commits

4adc87d Merge pull request #20685 from charris/prepare-for-1.22.0-release
fd66547 REL: Prepare for the NumPy 1.22.0 release.
125304b wip
c283859 Merge pull request #20682 from charris/backport-20416
5399c03 Merge pull request #20681 from charris/backport-20954
f9c45f8 Merge pull request #20680 from charris/backport-20663
794b36f Update armccompiler.py
d93b14e Update test_public_api.py
7662c07 Update init.py
311ab52 Update armccompiler.py
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dependencies

A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery

PiSL A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery. Sun, F., Liu, Y. and Sun, H., 2021. Physics-informe

8 Jul 13, 2022

This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEECH" submitted to ICASSP 2022

CPC_DeepCluster This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEEC

2 Sep 15, 2022

Bump numpy from 1.21 to 1.22.0 in /dangerous-words
Bumps numpy from 1.21 to 1.22.0.

Release notes

Sourced from numpy's releases.

v1.22.0

NumPy 1.22.0 Release Notes

NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.

A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.

NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.

New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.

A new configurable allocator for use by downstream projects.

These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

Expired deprecations

Deprecated numeric style dtype strings have been removed

Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

(gh-19539)

Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

(gh-19615)

... (truncated)

Commits

4adc87d Merge pull request #20685 from charris/prepare-for-1.22.0-release

fd66547 REL: Prepare for the NumPy 1.22.0 release.

125304b wip

c283859 Merge pull request #20682 from charris/backport-20416

5399c03 Merge pull request #20681 from charris/backport-20954

f9c45f8 Merge pull request #20680 from charris/backport-20663

794b36f Update armccompiler.py

d93b14e Update test_public_api.py

7662c07 Update init.py

311ab52 Update armccompiler.py

Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

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dependencies
opened by dependabot[bot] 0

FAVD: Featherweight Assisted Vulnerability Discovery

Related tags

Overview

FAVD: Featherweight Assisted Vulnerability Discovery

Repository Organization

Requirements

Citation

Acknowledgement

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Bump numpy from 1.21 to 1.22.0 in /dangerous-words

v1.22.0

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