Xiaofeng Qi

26 papers A 1B 3Misc 2Journal 17Unranked 3
YearRankTypeTitle / Venue / Authors
2025 conf
ICA3PP (8)
Zhengyu Liu, Fan Zhang, Fengzhe Zhang, Yanzhao Gao, Xiaofeng Qi, Xinyi Zhang, Shuaikang Hou
2025 B conf
SMC
Zhengyu Liu, Fan Zhang, Fengzhe Zhang, Yijing Song, Xiaofeng Qi, Yanzhao Gao, Xinyi Zhang
2025 J jnl
Frontiers Inf. Technol. Electron. Eng.
Li Chen, Fan Zhang, Guangwei Xie, Yanzhao Gao, Xiaofeng Qi, Mingqian Sun
2022 J jnl
IEEE Trans. Cybern.
Xiaofeng Qi, Junjie Hu, Lei Zhang, Sen Bai, Zhang Yi
2022 J jnl
Appl. Intell.
Yong Pi, Qian Li, Xiaofeng Qi, Dan Deng, Zhang Yi
2022 J jnl
Neurocomputing
Xiaofeng Qi, Fasheng Yi, Lei Zhang, Yao Chen, Yong Pi, Yuanyuan Chen, Jixiang Guo, Jianyong Wang, Quan Guo, Jilan Li, Yi Chen, Qing Lv, Zhang Yi
2022 J jnl
IEEE Trans. Neural Networks Learn. Syst.
Lituan Wang, Lei Zhang, Xiaofeng Qi, Zhang Yi
2022 J jnl
CoRR
Chen Chen, Nana Hou, Yuchen Hu, Heqing Zou, Xiaofeng Qi, Eng Siong Chng
2022 A conf
INTERSPEECH
Chen Chen, Nana Hou, Yuchen Hu, Heqing Zou, Xiaofeng Qi, Eng Siong Chng
2022 B conf
COLING
Xiaofeng Qi, Chao Li, Zhongping Liang, Jigang Liu, Cheng Zhang, Yuanxin Wei, Lin Yuan, Guang Yang, Lanxiao Huang, Min Li
2022 Misc conf
ICASSP
Chen Chen, Yuchen Hu, Nana Hou, Xiaofeng Qi, Heqing Zou, Eng Siong Chng
2022 J jnl
CoRR
Chen Chen, Yuchen Hu, Nana Hou, Xiaofeng Qi, Heqing Zou, Eng Siong Chng
2021 J jnl
Knowl. Based Syst.
Xiaofeng Qi, Junjie Hu, Zhang Yi
2020 J jnl
Neurocomputing
Yong Pi, Yao Chen, Dan Deng, Xiaofeng Qi, Jilan Li, Qing Lv, Zhang Yi
2020 J jnl
Medical Image Anal.
Lituan Wang, Lei Zhang, Minjuan Zhu, Xiaofeng Qi, Zhang Yi
2020 J jnl
J. Ambient Intell. Humaniz. Comput.
Xiaofeng Qi, Tiejun Cui, Liangshan Shao, Yuyan Xing
2019 J jnl
Medical Image Anal.
Xiaofeng Qi, Lei Zhang, Yao Chen, Yong Pi, Yi Chen, Qing Lv, Zhang Yi
2016 B conf
IJCNN
Dayiheng Liu, Jian Cheng Lv, Xiaofeng Qi, Jiangshu Wei
2016 conf
ACA
Xiaofeng Qi, Xingming Zhang, Kaijian Yuan
2006 J jnl
J. Am. Medical Informatics Assoc.
S. Trent Rosenbloom, Xiaofeng Qi, William R. Riddle, William E. Russell, Susan C. DonLevy, Dario A. Giuse, Aileen B. Sedman, Stephen Andrew Spooner
1998 J jnl
IEEE Trans. Neural Networks
Xiaofeng Qi, Francesco Palmieri
1998 J jnl
IEEE Trans. Neural Networks
Yong Gao, Xiaofeng Qi, Francesco Palmieri
1994 J jnl
IEEE Trans. Neural Networks
Xiaofeng Qi, Francesco Palmieri
1994 J jnl
IEEE Trans. Neural Networks
Xiaofeng Qi, Francesco Palmieri
1993 conf
ICGA
Xiaofeng Qi, Francesco Palmieri
1992 Misc conf
ICASSP
Xiaofeng Qi, Francesco Palmieri
tests/unit/test_decompile_scores.py
← Index tests/unit/test_decompile_scores.py python
"""Unit tests for bninja/analysis/scores.py — ObfuscationScores."""
import sys
import pytest
from unittest.mock import MagicMock

# Install binaryninja stubs before importing
from tests.unit.conftest_binja_stubs import (
    install_binja_stubs,
    HighLevelILOperation,
)
bn_mock = install_binja_stubs()

from redb.extractors.decompiler.bninja.analysis.scores import (
    ObfuscationScores,
    get_dominated_by,
    uses_mba,
)
import binaryninja.highlevelil as hlil_mod


# ============================================================================
# Helper: Mock HLIL instruction
# ============================================================================

class MockHLILInstruction(hlil_mod.HighLevelILInstruction):
    """Mock HLIL instruction with operation and operands."""
    def __init__(self, operation, operands=None):
        self.operation = operation
        self.operands = operands or []


class MockHLILBasicBlock:
    """Mock HLIL basic block for flattened score testing."""
    def __init__(self, incoming_edges=None, dominator_tree_children=None):
        self.incoming_edges = incoming_edges or []
        self.dominator_tree_children = dominator_tree_children or []


# ============================================================================
# 5a. ObfuscationScores
# ============================================================================


class TestFlattenedScore:
    def test_flattened_score_no_back_edges(self):
        """Linear CFG with no back edges -> score 0.0."""
        block = MockHLILBasicBlock(incoming_edges=[], dominator_tree_children=[])
        func = MagicMock()
        func.basic_blocks = [block]
        scores = ObfuscationScores(func)
        assert scores.flattened_score() == 0.0

    def test_flattened_score_with_loop(self):
        """CFG with a back edge -> score > 0.0."""
        block = MockHLILBasicBlock(dominator_tree_children=[])
        # Create a back edge: an incoming edge whose source is in the dominated set
        edge = MagicMock()
        edge.source = block  # source IS the dominator -> back edge
        block.incoming_edges = [edge]
        func = MagicMock()
        func.basic_blocks = [block]
        scores = ObfuscationScores(func)
        assert scores.flattened_score() > 0.0

    def test_flattened_score_fully_flat(self):
        """Flattened CFG: one block dominates all -> ratio close to 1.0."""
        children = [MockHLILBasicBlock() for _ in range(4)]
        root = MockHLILBasicBlock(dominator_tree_children=children)
        # Back edge from root incoming
        edge = MagicMock()
        edge.source = root
        root.incoming_edges = [edge]
        all_blocks = [root] + children
        func = MagicMock()
        func.basic_blocks = all_blocks
        scores = ObfuscationScores(func)
        assert scores.flattened_score() == pytest.approx(1.0)


class TestMBAScore:
    def test_mba_score_no_mixed_ops(self):
        """Instructions with only arithmetic -> score 0.0."""
        instr = MockHLILInstruction(HighLevelILOperation.HLIL_ADD, operands=[])
        func = MagicMock()
        func.instructions = [instr]
        scores = ObfuscationScores(func)
        assert scores.MBA_score() == 0.0

    def test_mba_score_mixed_ops(self):
        """Instructions with arithmetic + logic -> score > 0.0."""
        inner_logic = MockHLILInstruction(HighLevelILOperation.HLIL_XOR, operands=[])
        outer_arith = MockHLILInstruction(
            HighLevelILOperation.HLIL_ADD, operands=[inner_logic]
        )
        func = MagicMock()
        func.instructions = [outer_arith]
        scores = ObfuscationScores(func)
        assert scores.MBA_score() > 0.0

    def test_mba_score_all_mixed(self):
        """Every instruction has both -> score 1.0."""
        inner_logic = MockHLILInstruction(HighLevelILOperation.HLIL_NOT, operands=[])
        outer_arith = MockHLILInstruction(
            HighLevelILOperation.HLIL_SUB, operands=[inner_logic]
        )
        func = MagicMock()
        func.instructions = [outer_arith]
        scores = ObfuscationScores(func)
        assert scores.MBA_score() == 1.0


class TestGetDominatedBy:
    def test_get_dominated_by(self):
        child1 = MockHLILBasicBlock(dominator_tree_children=[])
        child2 = MockHLILBasicBlock(dominator_tree_children=[])
        root = MockHLILBasicBlock(dominator_tree_children=[child1, child2])
        result = get_dominated_by(root)
        assert root in result
        assert child1 in result
        assert child2 in result
        assert len(result) == 3


class TestUsesMBA:
    def test_uses_mba_arithmetic_only(self):
        instr = MockHLILInstruction(HighLevelILOperation.HLIL_ADD, operands=[])
        assert uses_mba(instr) is False

    def test_uses_mba_logic_only(self):
        instr = MockHLILInstruction(HighLevelILOperation.HLIL_XOR, operands=[])
        assert uses_mba(instr) is False

    def test_uses_mba_mixed(self):
        inner = MockHLILInstruction(HighLevelILOperation.HLIL_AND, operands=[])
        outer = MockHLILInstruction(HighLevelILOperation.HLIL_ADD, operands=[inner])
        assert uses_mba(outer) is True