Kari A. Clark

13 papers Journal 4Unranked 9
YearRankTypeTitle / Venue / Authors
2025 conf
ECOC
Kari A. Clark, Zun Htay, Zichuan Zhou, Amany Kassem, Andrea Pertoldi, Benjamin Rudin, Florian Ernaury, Izzat Darwazeh, Zhixin Liu
2025 J jnl
CoRR
Kari A. Clark, Zun Htay, Zichuan Zhou, Amany Kassem, Andrea Pertoldi, Benjamin Rudin, Florian Emaury, Izzat Darwazeh, Zhixin Liu
2024 J jnl
J. Opt. Commun. Netw.
Kari A. Clark, Zichuan Zhou, Zhixin Liu
2023 conf
OFC
Zichuan Zhou, Kari A. Clark, Ashish Verma, Yasuhiro Matsui, Zhixin Liu
2023 conf
OFC
Kari A. Clark, Zichuan Zhou, Zhixin Liu
2022 conf
OFC
Zichuan Zhou, Jinlong Wei, Kari A. Clark, Eric Sillekens, Callum Deakin, Ronit Sohanpal, Yuan Luo, Radan Slavík, Zhixin Liu
2021 conf
OFC
Zichuan Zhou, Kari A. Clark, Callum Deakin, Petros Laccotripes, Zhixin Liu
2021 conf
OFC
Zhixin Liu, Kari A. Clark
2021 conf
OFC
Thomas Gerard, Kari A. Clark, Adam C. Funnell, Kai Shi, Benn Thomsen, Philip M. Watts, Krzysztof Jozwik, István Haller, Hugh Williams, Paolo Costa, Hitesh Ballani
2021 J jnl
CoRR
Zichuan Zhou, Jinlong Wei, Kari A. Clark, Eric Sillekens, Callum Deakin, Ronit Sohanpal, Yuan Luo, Radan Slavík, Zhixin Liu
2019 J jnl
Opt. Switch. Netw.
Paris Andreades, Kari A. Clark, Philip M. Watts, Georgios Zervas
2018 conf
ECOC
Kari A. Clark, Hitesh Ballani, Polina Bayvel, Daniel Cletheroe, Thomas Gerard, István Haller, Krzysztof Jozwik, Kai Shi, Benn Thomsen, Philip M. Watts, Hugh Williams, Georgios Zervas, Paolo Costa, Zhixin Liu
2017 conf
AISTECS@HiPEAC
Kari A. Clark, Phill Watt
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 == []