Xiao-Cheng Liao

15 papers A 2B 1Journal 11Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
Appl. Soft Comput.
Xiang-Ling Chen, Ya-Hui Jia, Xiao-Cheng Liao, Wei-Neng Chen
2025 J jnl
IEEE Trans. Syst. Man Cybern. Syst.
Xiao-Cheng Liao, Wei-Neng Chen, Xiao-Qi Guo, Jinghui Zhong, Da-Jiang Wang
2025 J jnl
CoRR
Xiao-Cheng Liao, Yi Mei, Mengjie Zhang
2025 J jnl
CoRR
Xiao-Cheng Liao, Yi Mei, Mengjie Zhang, Xiang-Ling Chen
2025 J jnl
IEEE Trans. Artif. Intell.
Xiao-Cheng Liao, Xiao-Min Hu, Xiang-Ling Chen, Yi Mei, Ya-Hui Jia, Wei-Neng Chen
2025 J jnl
CoRR
Xiao-Cheng Liao, Yi Mei, Mengjie Zhang
2024 A conf
GECCO
Xiang-Ling Chen, Xiao-Cheng Liao, Feng-Feng Wei, Wei-Neng Chen
2024 J jnl
CoRR
Xiao-Cheng Liao, Wei-Neng Chen, Xiang-Ling Chen, Yi Mei
2024 A conf
GECCO
Xiao-Cheng Liao, Yi Mei, Mengjie Zhang
2024 J jnl
CoRR
Xiao-Cheng Liao, Yi Mei, Mengjie Zhang
2024 J jnl
IEEE Trans. Emerg. Top. Comput. Intell.
Xiao-Cheng Liao, Wei-Neng Chen, Ya-Hui Jia, Wen-Jin Qiu
2024 J jnl
IEEE Trans. Comput. Soc. Syst.
Xiao-Cheng Liao, Ya-Hui Jia, Xiao-Min Hu, Wei-Neng Chen
2023 J jnl
IEEE Trans. Intell. Transp. Syst.
Xiao-Cheng Liao, Wei-Neng Chen, Xiao-Qi Guo, Jinghui Zhong, Xiao-Min Hu
2023 B conf
SMC
Xiang-Ling Chen, Xiao-Cheng Liao, Wei-Neng Chen
2022 conf
ICONIP (6)
Xiao-Cheng Liao, Wen-Jin Qiu, Feng-Feng Wei, Wei-Neng Chen
redb/extractors/decompiler/bninja/analysis/medium_level_normalization.py
← Index redb/extractors/decompiler/bninja/analysis/medium_level_normalization.py python
from binaryninja import (
    MediumLevelILInstruction,
    Variable, SSAVariable,
    ILIntrinsic,
)


class MediumLevelNormalization:
    def __init__(self):
        return

    def _collect_ops(self, il, ops):
        if il is None:
            return
        ops.append(int(il.operation))
        operands = getattr(il, "operands", None)
        if not operands:
            return
        for op in operands:
            if isinstance(op, MediumLevelILInstruction):
                self._collect_ops(op, ops)
            elif isinstance(op, (list, tuple)):
                for sub in op:
                    if isinstance(sub, MediumLevelILInstruction):
                        self._collect_ops(sub, ops)

    def normalize_instruction_all_levels(self, instr_il):
        ops = []
        self._collect_ops(instr_il, ops)
        return ops

    def _leaf_type(self, val):
        if isinstance(val, SSAVariable):
            return "SSA_VAR"
        if isinstance(val, Variable):
            return "VAR"
        if isinstance(val, ILIntrinsic):
            return "INTRINSIC"
        if isinstance(val, bool):
            return "BOOL"
        if isinstance(val, float):
            return "FLOAT_CONST"
        if isinstance(val, int):
            return "CONST"
        if isinstance(val, str):
            return "STR"
        return type(val).__name__.upper()

    def _collect(self, il, out_op):
        if il is None:
            return
        out_op.append(int(il.operation))
        operands = getattr(il, "operands", None)
        if not operands:
            return
        for op in operands:
            if isinstance(op, MediumLevelILInstruction):
                self._collect(op, out_op)
            elif isinstance(op, (list, tuple)):
                for sub in op:
                    if isinstance(sub, MediumLevelILInstruction):
                        self._collect(sub, out_op)
                    else:
                        out_op.append(self._leaf_type(sub))
            else:
                out_op.append(self._leaf_type(op))

    def normalize_instr_with_operands(self, instr_il):
        ops = []
        self._collect(instr_il, ops)
        return ops