Hailun Zhang

34 papers A* 2A 4C 1Misc 1Journal 20Unranked 6
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Xiwen Wang, Shichao Zhang, Hailun Zhang, Ruowei Wang, Mao Li, Chenyu Zhou, Qijun Zhao, Ji-Zhe Zhou
2026 A* conf
AAAI
Yujiao Hu, Zuyu Chen, Mengjie Lee, Jinchao Chen, Meng Shen, Hailun Zhang, Wei Li, Yan Pan
2026 A* conf
AAAI
Yue Yang, Song Tang, Qijun Zhao, Hailun Zhang, Xiwen Wang, Zijian Deng
2025 conf
PRCV (7)
Lingjie Zeng, Hailun Zhang, Xinrui Wang, Zhen Zhai, Qijun Zhao, Hanyang Lin
2025 Misc conf
ICASSP
Hailun Zhang, Xinrui Wang, Qijun Zhao
2025 A conf
ICME
Hailun Zhang, Qijun Zhao, Zhen Zhai, Xinrui Wang
2025 J jnl
Int. J. Prod. Res.
Jie Liu, Hailun Zhang, Baozhuang Niu
2025 conf
ASP-DAC
Shibo Chen, Hailun Zhang, Todd M. Austin
2024 J jnl
IEEE Trans. Intell. Transp. Syst.
Hailun Zhang, Rui Fu, Chang Wang, Yingshi Guo, Wei Yuan
2024 J jnl
IEEE Trans. Veh. Technol.
Rui Fu, Bing Yang, Hailun Zhang, Eryuan Liu
2024 J jnl
Technol. Anal. Strateg. Manag.
Hailun Zhang
2024 J jnl
Oper. Res.
Guangju Wang, Hailun Zhang, Jiheng Zhang
2024 J jnl
Int. J. Prod. Res.
Baozhuang Niu, Nan Zhang, Fengfeng Xie, Hailun Zhang
2024 conf
PRICAI (4)
Shanfeng Zhou, Bo Yuan, Keren Fu, Hailun Zhang, Qijun Zhao
2024 conf
PRCV (7)
Zhen Zhai, Hailun Zhang, Qijun Zhao, Keren Fu
2024 J jnl
Oper. Res.
Zhenghua Long, Hailun Zhang, Jiheng Zhang, Zhe George Zhang
2023 A conf
ICME
Hailun Zhang, Ziyun Zeng, Qijun Zhao, Zhen Zhai
2023 A conf
ICME
Yiwen Zhang, Hailun Zhang, Qijun Zhao
2023 J jnl
npj Digit. Medicine
Jing Xu, Jiarui Ou, Chen Li, Zheng Zhu, Jian Li, Hailun Zhang, Junchen Chen, Bin Yi, Wu Zhu, Weiru Zhang, Guanxiong Zhang, Qian Gao, Yehong Kuang, Jiangning Song, Xiang Chen, Hong Liu
2023 J jnl
Oper. Res. Lett.
Lixiang Li, Min Li, Hailun Zhang, Lianmin Zhang
2022 A conf
ICME
Tao Ding, Qijun Zhao, Feng Liu, Hailun Zhang, Pengyu Peng
2022 J jnl
IEEE Trans. Intell. Transp. Syst.
Hailun Zhang, Rui Fu
2022 J jnl
Entropy
Bin Yang, Xiaojing Ma, Hailun Zhang, Wenxu Sun, Lei Jia, Haoyuan Xue
2022 J jnl
Appl. Math. Comput.
Tao You, Hailun Zhang, Ying Zhang, Qing Li, Peng Zhang, Mei Yang
2022 J jnl
IEEE Internet Things J.
Hailun Zhang, Rui Fu, Chang Wang, Yingshi Guo, Wei Yuan
2021 J jnl
Comput. Commun.
Hailun Zhang, Rui Fu
2020 J jnl
Sensors
Hailun Zhang, Rui Fu
2020 J jnl
Oper. Res.
Zhenghua Long, Nahum Shimkin, Hailun Zhang, Jiheng Zhang
2020 J jnl
CoRR
Yuhao Zhou, Qing Ye, Hailun Zhang, Jiancheng Lv
2020 conf
ICONIP (2)
Yuhao Zhou, Qing Ye, Hailun Zhang, Jiancheng Lv
2020 J jnl
Manag. Sci.
Zhen Xu, Hailun Zhang, Rachel Q. Zhang
2020 J jnl
IEEE Access
Ning Wang, Wei Feng, Hailun Zhang, Shumin Li
2013 conf
ICIA
Xingguang Qi, Xiaoting Li, Hailun Zhang
2012 C conf
HIS
Jing He, Yanchun Zhang, Guangyan Huang, Yefei Xin, Xiaohui Liu, Hao Lan Zhang, Stanley Chiang, Hailun Zhang
redb/extractors/decompiler/bninja/analysis/cfg.py
← Index redb/extractors/decompiler/bninja/analysis/cfg.py python
from binaryninja.enums import LowLevelILOperation as LLIL_OP

# Support both package and standalone imports
try:
    from . import cfg_features
except ImportError:
    from redb.extractors.decompiler.bninja.analysis import cfg_features


# ---------------------------------------------------------------------------
# Task 2.2: Build LLIL operation maps at import time using real enum values
# ---------------------------------------------------------------------------

# Prime product map: LLIL operation integer value -> small prime
cfg_features.LLIL_OP_PRIMES = {
    # SET_REG, SET_REG_SPLIT
    LLIL_OP.LLIL_SET_REG.value: 2,
    LLIL_OP.LLIL_SET_REG_SPLIT.value: 2,
    # SET_FLAG
    LLIL_OP.LLIL_SET_FLAG.value: 3,
    # LOAD
    LLIL_OP.LLIL_LOAD.value: 5,
    # STORE
    LLIL_OP.LLIL_STORE.value: 7,
    # PUSH, POP
    LLIL_OP.LLIL_PUSH.value: 11,
    LLIL_OP.LLIL_POP.value: 13,
    # CALL, TAILCALL, SYSCALL
    LLIL_OP.LLIL_CALL.value: 17,
    LLIL_OP.LLIL_TAILCALL.value: 17,
    LLIL_OP.LLIL_SYSCALL.value: 19,
    # RET, NORET
    LLIL_OP.LLIL_RET.value: 23,
    LLIL_OP.LLIL_NORET.value: 23,
    # IF, GOTO
    LLIL_OP.LLIL_IF.value: 29,
    LLIL_OP.LLIL_GOTO.value: 31,
    # ADD, SUB
    LLIL_OP.LLIL_ADD.value: 37,
    LLIL_OP.LLIL_SUB.value: 41,
    # AND, OR, XOR
    LLIL_OP.LLIL_AND.value: 43,
    LLIL_OP.LLIL_OR.value: 47,
    LLIL_OP.LLIL_XOR.value: 53,
    # LSL, LSR, ASR, ROL, ROR
    LLIL_OP.LLIL_LSL.value: 59,
    LLIL_OP.LLIL_LSR.value: 61,
    LLIL_OP.LLIL_ASR.value: 67,
    LLIL_OP.LLIL_ROL.value: 71,
    LLIL_OP.LLIL_ROR.value: 73,
    # MUL, DIVU, DIVS, MODU, MODS
    LLIL_OP.LLIL_MUL.value: 79,
    LLIL_OP.LLIL_DIVU.value: 83,
    LLIL_OP.LLIL_DIVS.value: 83,
    LLIL_OP.LLIL_MODU.value: 89,
    LLIL_OP.LLIL_MODS.value: 89,
    # NEG, NOT
    LLIL_OP.LLIL_NEG.value: 97,
    LLIL_OP.LLIL_NOT.value: 101,
    # CMP_E, CMP_NE, CMP_SLT, CMP_ULT, CMP_SLE, CMP_ULE
    # CMP_SGT, CMP_UGT, CMP_SGE, CMP_UGE
    LLIL_OP.LLIL_CMP_E.value: 103,
    LLIL_OP.LLIL_CMP_NE.value: 103,
    LLIL_OP.LLIL_CMP_SLT.value: 107,
    LLIL_OP.LLIL_CMP_ULT.value: 107,
    LLIL_OP.LLIL_CMP_SLE.value: 109,
    LLIL_OP.LLIL_CMP_ULE.value: 109,
    LLIL_OP.LLIL_CMP_SGT.value: 113,
    LLIL_OP.LLIL_CMP_UGT.value: 113,
    LLIL_OP.LLIL_CMP_SGE.value: 127,
    LLIL_OP.LLIL_CMP_UGE.value: 127,
    # NOP
    LLIL_OP.LLIL_NOP.value: 1,
    # SX, ZX, LOW_PART, BOOL_TO_INT
    LLIL_OP.LLIL_SX.value: 131,
    LLIL_OP.LLIL_ZX.value: 137,
    LLIL_OP.LLIL_LOW_PART.value: 139,
    LLIL_OP.LLIL_BOOL_TO_INT.value: 149,
    # JUMP, JUMP_TO
    LLIL_OP.LLIL_JUMP.value: 151,
    LLIL_OP.LLIL_JUMP_TO.value: 151,
}

# Category map: LLIL operation integer value -> category index
_ARITHMETIC = {
    LLIL_OP.LLIL_ADD, LLIL_OP.LLIL_ADC, LLIL_OP.LLIL_SUB, LLIL_OP.LLIL_SBB,
    LLIL_OP.LLIL_MUL, LLIL_OP.LLIL_MULU_DP, LLIL_OP.LLIL_MULS_DP,
    LLIL_OP.LLIL_DIVU, LLIL_OP.LLIL_DIVU_DP, LLIL_OP.LLIL_DIVS,
    LLIL_OP.LLIL_DIVS_DP, LLIL_OP.LLIL_MODU, LLIL_OP.LLIL_MODS,
    LLIL_OP.LLIL_NEG,
}
_LOGIC = {
    LLIL_OP.LLIL_AND, LLIL_OP.LLIL_OR, LLIL_OP.LLIL_XOR, LLIL_OP.LLIL_NOT,
    LLIL_OP.LLIL_LSL, LLIL_OP.LLIL_LSR, LLIL_OP.LLIL_ASR,
    LLIL_OP.LLIL_ROL, LLIL_OP.LLIL_RLC, LLIL_OP.LLIL_ROR, LLIL_OP.LLIL_RRC,
}
_TRANSFER = {
    LLIL_OP.LLIL_SET_REG, LLIL_OP.LLIL_SET_REG_SPLIT, LLIL_OP.LLIL_SET_FLAG,
    LLIL_OP.LLIL_GOTO, LLIL_OP.LLIL_IF, LLIL_OP.LLIL_JUMP, LLIL_OP.LLIL_JUMP_TO,
    LLIL_OP.LLIL_RET, LLIL_OP.LLIL_NORET, LLIL_OP.LLIL_PUSH, LLIL_OP.LLIL_POP,
}
_CALL = {
    LLIL_OP.LLIL_CALL, LLIL_OP.LLIL_TAILCALL, LLIL_OP.LLIL_SYSCALL,
}
_COMPARISON = {
    LLIL_OP.LLIL_CMP_E, LLIL_OP.LLIL_CMP_NE,
    LLIL_OP.LLIL_CMP_SLT, LLIL_OP.LLIL_CMP_ULT,
    LLIL_OP.LLIL_CMP_SLE, LLIL_OP.LLIL_CMP_ULE,
    LLIL_OP.LLIL_CMP_SGE, LLIL_OP.LLIL_CMP_UGE,
    LLIL_OP.LLIL_CMP_SGT, LLIL_OP.LLIL_CMP_UGT,
    LLIL_OP.LLIL_TEST_BIT, LLIL_OP.LLIL_FLAG_COND,
}
_MEMORY = {
    LLIL_OP.LLIL_LOAD, LLIL_OP.LLIL_STORE,
}

cfg_features.LLIL_OP_CATEGORIES = {}
for _op in _ARITHMETIC:
    cfg_features.LLIL_OP_CATEGORIES[_op.value] = cfg_features.CAT_ARITHMETIC
for _op in _LOGIC:
    cfg_features.LLIL_OP_CATEGORIES[_op.value] = cfg_features.CAT_LOGIC
for _op in _TRANSFER:
    cfg_features.LLIL_OP_CATEGORIES[_op.value] = cfg_features.CAT_TRANSFER
for _op in _CALL:
    cfg_features.LLIL_OP_CATEGORIES[_op.value] = cfg_features.CAT_CALL
for _op in _COMPARISON:
    cfg_features.LLIL_OP_CATEGORIES[_op.value] = cfg_features.CAT_COMPARISON
for _op in _MEMORY:
    cfg_features.LLIL_OP_CATEGORIES[_op.value] = cfg_features.CAT_MEMORY

# Set of CALL operation values for counting
_CALL_OPS = {op.value for op in _CALL}


# ---------------------------------------------------------------------------
# Task 2.1 + 2.3: Rewritten CFGAnalysis
# ---------------------------------------------------------------------------

class CFGAnalysis:
    def __init__(self, function, llil_function=None):
        self.function = function
        self.llil_function = llil_function

    def extract_function_cfg(self):
        """Extract function-level CFG features as a flat dictionary."""

        if self.function is None:
            return None

        blocks = list(self.function.basic_blocks)
        if not blocks:
            return None

        n = len(blocks)

        # 1. Build index-based adjacency from Binary Ninja blocks
        addr_to_idx = {b.start: i for i, b in enumerate(blocks)}
        successors = [[] for _ in range(n)]
        predecessors = [[] for _ in range(n)]
        for i, block in enumerate(blocks):
            for edge in block.outgoing_edges:
                if edge.target is None:
                    continue
                target_idx = addr_to_idx.get(edge.target.start)
                if target_idx is not None:
                    successors[i].append(target_idx)
                    predecessors[target_idx].append(i)

        # 2. BFS order (reusable across multiple features)
        bfs = cfg_features.bfs_order(successors, n)

        # 3. Collect per-block LLIL operations (for prime product + ACFG features)
        block_llil_ops = self._collect_block_llil_ops(blocks, addr_to_idx, n)
        all_llil_ops = [op for block_ops in block_llil_ops for op in block_ops]

        # 4. Structural counts
        edge_count = sum(len(s) for s in successors)
        total_llil = sum(len(ops) for ops in block_llil_ops)
        call_count = sum(
            1 for ops in block_llil_ops for op in ops
            if op in _CALL_OPS
        )

        # 5. Compute all features
        bb_features = cfg_features.build_block_features(block_llil_ops, successors, n)

        return {
            "cfg_topology_hash": cfg_features.compute_topology_hash(successors, bfs, n),
            "block_count": n,
            "edge_count": edge_count,
            "llil_total_operations": total_llil,
            "call_count": call_count,
            "cyclomatic_complexity": edge_count - n + 2,
            "loop_count": cfg_features.count_back_edges(successors, n),
            "max_depth": cfg_features.bfs_max_depth(successors, n),
            "max_fan_out": max((len(s) for s in successors), default=0),
            "md_index_topdown": cfg_features.compute_md_index_topdown(successors, predecessors, bfs),
            "md_index_bottomup": cfg_features.compute_md_index_bottomup(successors, predecessors, n),
            "prime_product_llil": cfg_features.compute_prime_product(all_llil_ops),
            "cfg_feature_tlsh": cfg_features.compute_cfg_feature_tlsh(bb_features, bfs),
            "wl_minhash": cfg_features.compute_wl_minhash(successors, predecessors, bb_features, n),
            "bb_features": bb_features,
            "cfg_adjacency": cfg_features.pack_adjacency(successors),
        }

    def _collect_block_llil_ops(self, blocks, addr_to_idx, n):
        """
        Collect LLIL operation integers per native basic block.
        Walks the full expression tree of each instruction so that
        nested operations (e.g. ADD inside SET_REG) are captured.
        Returns list of n lists, one per block.
        """
        block_ops = [[] for _ in range(n)]

        if self.llil_function is None:
            return block_ops

        try:
            for llil_block in self.llil_function.basic_blocks:
                # Map LLIL block to native block via source_block
                if llil_block.source_block is not None:
                    native_idx = addr_to_idx.get(llil_block.source_block.start)
                    if native_idx is not None:
                        for instr in llil_block:
                            self._walk_llil_ops(instr, block_ops[native_idx])
        except Exception:
            pass  # Return empty ops — LLIL-dependent fields will be 0/null

        return block_ops

    @staticmethod
    def _walk_llil_ops(expr, ops_list):
        """Collect operation values from an LLIL expression tree iteratively."""
        stack = [expr]
        while stack:
            node = stack.pop()
            if hasattr(node, 'operation'):
                ops_list.append(node.operation.value)
            if hasattr(node, 'operands'):
                for operand in node.operands:
                    if hasattr(operand, 'operation'):
                        stack.append(operand)