Ilya A. Rybak

20 papers C 1Misc 1Journal 16Unranked 2
YearRankTypeTitle / Venue / Authors
2021 J jnl
IEEE Access
Shravan Tata Ramalingasetty, Simon M. Danner, Jonathan Arreguit, Sergey N. Markin, Dimitri Rodarie, Claudia Kathe, Grégoire Courtine, Ilya A. Rybak, Auke Jan Ijspeert
2018 J jnl
PLoS Comput. Biol.
Jessica Ausborn, Hidehiko Koizumi, William H. Barnett, Tibin T. John, Ruli Zhang, Yaroslav I. Molkov, Jeffrey C. Smith, Ilya A. Rybak
2017 J jnl
Frontiers Comput. Neurosci.
Taegyo Kim, Khaldoun C. Hamade, Dmitry Todorov, William H. Barnett, Robert A. Capps, Elizaveta M. Latash, Sergey N. Markin, Ilya A. Rybak, Yaroslav I. Molkov
2015 J jnl
PLoS Comput. Biol.
Yaroslav I. Molkov, Bartholomew J. Bacak, Adolfo E. Talpalar, Ilya A. Rybak
2011 J jnl
J. Comput. Neurosci.
Jonathan E. Rubin, Bartholomew J. Bacak, Yaroslav I. Molkov, Natalia Shevtsova, Jeffrey C. Smith, Ilya A. Rybak
2010 J jnl
Neurocomputing
Witali L. Dunin-Barkowski, Andrew T. Lovering, John M. Orem, David M. Baekey, Thomas E. Dick, Ilya A. Rybak, Kendall Francis Morris, Russell O'Connor, Sarah C. Nuding, Roger Shannon, Bruce G. Lindsey
2009 J jnl
J. Comput. Neurosci.
Silvia Daun, Jonathan E. Rubin, Ilya A. Rybak
2004 J jnl
Biol. Cybern.
Ilya A. Rybak, Natalia Shevtsova, Krzysztof Ptak, Donald R. McCrimmon
2003 J jnl
Neurocomputing
Natalia Shevtsova, Krzysztof Ptak, Donald R. McCrimmon, Ilya A. Rybak
2003 J jnl
Neurocomputing
Dmitry G. Ivashko, Boris I. Prilutsky, Sergey N. Markin, John K. Chapin, Ilya A. Rybak
2002 J jnl
Neurocomputing
Ilya A. Rybak, Julian F. R. Paton, R. F. Rogers, Walter M. St.-John
2002 C conf
ICANN
Ilya A. Rybak, Dmitry G. Ivashko, Boris I. Prilutsky, M. Anthony Lewis, John K. Chapin
2001 J jnl
Robotics Auton. Syst.
Simon F. Giszter, Karen A. Moxon, Ilya A. Rybak, John K. Chapin
2000 J jnl
IEEE Intell. Syst.
Simon F. Giszter, Karen A. Moxon, Ilya A. Rybak, John K. Chapin
1997 J jnl
Neural Comput.
Harpreet S. Kwatra, Francis J. Doyle III, Ilya A. Rybak, James S. Schwaber
1995 Misc conf
IWANN
Ilya A. Rybak, Julian F. R. Paton, James S. Schwaber
1994 conf
ICPR (2)
Ilya A. Rybak, Valentina I. Gusakova, Alexander V. Golovan, Natalia Shevtsova, Lubov Podladchikova
1994 conf
ICPR (2)
Alain Faure, Natalia Shevtsova, Alexander V. Golovan, Arkadi A. Klepatch, Olga Cachard, Ilya A. Rybak
1992 J jnl
Neurocomputing
Ilya A. Rybak, Natalia Shevtsova, Vladislav M. Sandler
1991 J jnl
Neural Networks
Ilya A. Rybak, Natalia Shevtsova, Lubov N. Podladchikova, Alexander V. Golovan
tests/unit/test_decompile_utils.py
← Index tests/unit/test_decompile_utils.py python
"""Unit tests for decompiler utility modules:
- bninja/utils/hashes.py
- bninja/utils/json_encoder.py
- bninja/analysis/low_level_normalization.py
"""
import hashlib
import json
import pytest


# ============================================================================
# 1a. hashes.py
# ============================================================================

from redb.extractors.decompiler.bninja.utils.hashes import (
    calculate_md5,
    calculate_sha256,
    calculate_tlsh,
)


class TestCalculateMD5:
    def test_calculate_md5_known_value(self):
        expected = hashlib.md5(b"test").hexdigest()
        assert calculate_md5("test") == expected

    def test_calculate_md5_empty(self):
        expected = hashlib.md5(b"").hexdigest()
        assert calculate_md5("") == expected


class TestCalculateSHA256:
    def test_calculate_sha256_known_value(self):
        expected = hashlib.sha256(b"hello world").hexdigest()
        assert calculate_sha256("hello world") == expected

    def test_calculate_sha256_empty_string(self):
        result = calculate_sha256("")
        assert len(result) == 64
        assert all(c in "0123456789abcdef" for c in result)


class TestCalculateTLSH:
    def test_calculate_tlsh_long_data(self):
        # TLSH requires >= 50 bytes
        data = "A" * 100
        result = calculate_tlsh(data)
        assert result is not None
        assert isinstance(result, str)

    def test_calculate_tlsh_short_data(self):
        data = "A" * 10
        result = calculate_tlsh(data)
        assert result is None

    def test_calculate_tlsh_deterministic(self):
        data = "x" * 200
        assert calculate_tlsh(data) == calculate_tlsh(data)



# ============================================================================
# 1b. json_encoder.py
# ============================================================================

from redb.extractors.decompiler.bninja.utils.json_encoder import BinaryNinjaEncoder


class TestBinaryNinjaEncoder:
    def test_encode_value_confidence_object(self):
        obj = type("VC", (), {"value": 42, "confidence": 255})()
        result = json.dumps(obj, cls=BinaryNinjaEncoder)
        assert json.loads(result) == 42

    def test_encode_str_fallback(self):
        obj = type("Obj", (), {"__str__": lambda self: "custom_repr"})()
        result = json.dumps(obj, cls=BinaryNinjaEncoder)
        assert json.loads(result) == "custom_repr"

    def test_encode_normal_types(self):
        data = {"a": 1, "b": [2, 3], "c": "hello"}
        result = json.dumps(data, cls=BinaryNinjaEncoder)
        assert json.loads(result) == data

    def test_encode_set_via_str(self):
        # Python sets have __str__, so BinaryNinjaEncoder converts them
        # to their string repr instead of raising TypeError.
        result = json.dumps(set([1, 2, 3]), cls=BinaryNinjaEncoder)
        parsed = json.loads(result)
        assert isinstance(parsed, str)
        assert "1" in parsed


# ============================================================================
# 1c. low_level_normalization.py
# ============================================================================

from redb.extractors.decompiler.bninja.analysis.low_level_normalization import (
    LowLevelNormalization,
)


class MockIL:
    """Mock IL node for normalization tests."""
    def __init__(self, operation, operands=None):
        self.operation = operation
        self.operands = operands or []


class TestLowLevelNormalization:
    def setup_method(self):
        self.normalizer = LowLevelNormalization()

    def test_normalize_single_instruction(self):
        node = MockIL(operation=5)
        result = self.normalizer.normalize_instruction_all_levels(node)
        assert result == [5]

    def test_normalize_nested_operands(self):
        child1 = MockIL(operation=10)
        child2 = MockIL(operation=20)
        root = MockIL(operation=1, operands=[child1, child2])
        result = self.normalizer.normalize_instruction_all_levels(root)
        assert result == [1, 10, 20]

    def test_normalize_empty_operands(self):
        node = MockIL(operation=42, operands=[])
        result = self.normalizer.normalize_instruction_all_levels(node)
        assert result == [42]

    def test_normalize_list_operands(self):
        # Simulates phi-node style list operands
        inner = MockIL(operation=99)
        node = MockIL(operation=7, operands=[[inner]])
        result = self.normalizer.normalize_instruction_all_levels(node)
        assert result == [7, 99]

    def test_normalize_none_input(self):
        result = self.normalizer.normalize_instruction_all_levels(None)
        assert result == []