Commit 8fe310f8 authored by Rémi Huguet's avatar Rémi Huguet
Browse files

fix: remove unused private APIs

parent 9358e52e

scared/__init__.py

+1 −2
Original line number Diff line number Diff line
@@ -21,11 +21,10 @@ from .analysis import ( # noqa:F401 
    BaseAttack, CPAAttack, DPAAttack,

    ANOVAAttack, NICVAttack, SNRAttack,

    BasePartitionedAttack, MIAAttack,

    _Attack,

    BaseReverse, CPAReverse, DPAReverse,

    ANOVAReverse, NICVReverse, SNRReverse,

    BasePartitionedReverse, MIAReverse,

    _Reverse, TemplateAttack, TemplateDPAAttack

    TemplateAttack, TemplateDPAAttack

)

from .preprocesses import preprocess, Preprocess, PreprocessError  # noqa:F401

from . import preprocesses  # noqa: F401

scared/analysis/__init__.py

+1 −1
Original line number Diff line number Diff line
@@ -8,4 +8,4 @@ from ._analysis import ( # noqa: F401 
    MIAAttack, MIAReverse

)

from .template import TemplateAttack, TemplateDPAAttack, BaseTemplateAttack  # noqa: F401

from .base import BaseAttack, BasePartitionedAttack, BasePartitionedReverse, BaseReverse, _Attack, _Reverse   # noqa: F401
 
from .base import BaseAttack, BasePartitionedAttack, BasePartitionedReverse, BaseReverse   # noqa: F401

scared/analysis/base.py

+0 −34
Original line number Diff line number Diff line
@@ -250,40 +250,6 @@ class BaseReverse(_BaseAnalysis): 
    pass





class _MetaAnalysis:



    def __new__(cls, distinguisher, *args, **kwargs):

        klass = type.__new__(type, f'{distinguisher.__class__.__name__}Analysis', (cls._base_klass, type(distinguisher).__bases__[1]), {})

        obj = klass(*args, **kwargs)

        init_args = inspect.getfullargspec(type(distinguisher)).args

        values = inspect.getmembers(distinguisher)

        for arg in init_args[1:]:

            val = list(filter(lambda t: t[0] == arg, values))[0]

            if val:

                setattr(obj, arg, val[1])

        return obj





class _Attack(_MetaAnalysis):

    """Returns an analysis object created from a standalone distinguisher.



    It has been implemented for backward compatibility with previous eshard libraries and is not intented as a public API.



    """



    _base_klass = BaseAttack





class _Reverse(_MetaAnalysis):

    """Returns an analysis object created from a standalone distinguisher.



    It has been implemented for backward compatibility with previous eshard libraries and is not intented as a public API.



    """



    _base_klass = BaseReverse





class BasePartitionedReverse(BaseReverse):

    def __init__(self, partitions=None, *args, **kwargs):

        distinguishers.partitioned._set_partitions(self, partitions)

tests/test_attacks_analysis.py

+0 −23
Original line number Diff line number Diff line
@@ -518,26 +518,3 @@ def test_mia_bin_edges_init(sf): 
    a = scared.MIAAttack(bin_edges=np.arange(258), selection_function=sf, model=scared.HammingWeight(), discriminant=scared.abssum)

    assert np.array_equal(a.bin_edges, np.arange(258))

    assert isinstance(str(a), str)
 




def test_analysis_created_with_standalone_distinguisher(sf, container):

    d = scared.CPADistinguisher()

    analysis = scared._Attack(distinguisher=d, selection_function=sf, discriminant=scared.maxabs, model=scared.Monobit(4), convergence_step=150)



    analysis.run(container)

    assert (256, 16, 2) == analysis.convergence_traces.shape

    assert (256, 16) == analysis.results.shape[0:2]

    assert (256, 16) == analysis.scores.shape

    assert np.array_equal(analysis.scores, analysis.convergence_traces[:, :, -1])

    assert isinstance(str(d), str)



    d = scared.ANOVADistinguisher(precision='float64', partitions=np.arange(2))

    analysis = scared._Attack(distinguisher=d, selection_function=sf, discriminant=scared.maxabs, model=scared.Monobit(4), convergence_step=150)

    analysis.run(container)

    assert analysis.precision == 'float64'

    assert np.array_equal(analysis.partitions, np.arange(2))

    assert (256, 16, 2) == analysis.convergence_traces.shape

    assert (256, 16) == analysis.results.shape[0:2]

    assert (256, 16) == analysis.scores.shape

    assert np.array_equal(analysis.scores, analysis.convergence_traces[:, :, -1])

    assert isinstance(str(d), str)

tests/test_reverses_analysis.py

+0 −17
Original line number Diff line number Diff line
@@ -260,20 +260,3 @@ def test_mia_bin_edges_init(sf): 
    a = scared.MIAReverse(bin_edges=np.arange(258), selection_function=sf, model=scared.HammingWeight())

    assert np.array_equal(a.bin_edges, np.arange(258))

    assert isinstance(str(a), str)
 




def test_analysis_created_with_standalone_distinguisher(sf, container):

    d = scared.CPADistinguisher()

    analysis = scared._Reverse(distinguisher=d, selection_function=sf, model=scared.Monobit(4))



    analysis.run(container)

    assert (16,) == analysis.results.shape[0:1]

    assert isinstance(str(d), str)



    d = scared.ANOVADistinguisher(precision='float64', partitions=np.arange(2))

    analysis = scared._Reverse(distinguisher=d, selection_function=sf, model=scared.Monobit(4))

    analysis.run(container)

    assert analysis.precision == 'float64'

    assert np.array_equal(analysis.partitions, np.arange(2))

    assert (16,) == analysis.results.shape[0:1]

    assert isinstance(str(d), str)