Han Cong Feng

12 papers Journal 12
YearRankTypeTitle / Venue / Authors
2025 J jnl
Expert Syst. Appl.
Han Cong Feng, Kaili Jiang, Yuxin Zhao, Kailun Tian, Bin Tang
2025 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Han Cong Feng, Kai Li Jiang, Zhixin Zhou, Yuxin Zhao, Kailun Tian, Bin Tang
2025 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Yuxin Zhao, Zhanlei Zhu, Han Cong Feng, Kailun Tian, Kaili Jiang, Bin Tang
2024 J jnl
Remote. Sens.
Kaili Jiang, Dechang Wang, Kailun Tian, Yuxin Zhao, Han Cong Feng, Bin Tang
2024 J jnl
IEEE Trans. Wirel. Commun.
Kaili Jiang, Kailun Tian, Han Cong Feng, Yuxin Zhao, Dechang Wang, Jian Gao, Sen Cao, Xuying Zhang, Yanfei Li, Junyu Yuan, Ying Xiong, Bin Tang
2024 J jnl
Remote. Sens.
Mohammed Khalafalla, Kaili Jiang, Kailun Tian, Han Cong Feng, Ying Xiong, Bin Tang
2024 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Han Cong Feng, Kai Li Jiang, Zhixin Zhou, Yuxin Zhao, Hai Xin Yan, Kailun Tian, Bin Tang
2024 J jnl
Remote. Sens.
Mohammed Khalafalla, Kaili Jiang, Kailun Tian, Han Cong Feng, Ying Xiong, Bin Tang
2024 J jnl
IEEE Internet Things J.
Kaili Jiang, Dechang Wang, Kailun Tian, Han Cong Feng, Yuxin Zhao, Sen Cao, Jian Gao, Xuying Zhang, Yanfei Li, Junyu Yuan, Ying Xiong, Bin Tang
2023 J jnl
Remote. Sens.
Yuxin Zhao, Han Cong Feng, Kaili Jiang, Bin Tang
2023 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Han Cong Feng, Kai Li Jiang, Yu Xin Zhao, Abdulrahman Q. S. Al-Malahi, Bin Tang
2022 J jnl
Digit. Signal Process.
Han Cong Feng, Bin Tang, Tao Wan
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 == []