Weijiang Lai

11 papers A* 1A 2Journal 4Unranked 4
YearRankTypeTitle / Venue / Authors
2026 A* conf
WWW
Weijiang Lai, Beihong Jin, Di Zhang, Siru Chen, Jiongyan Zhang, Yuhang Gou, Jian Dong, Xingxing Wang
2026 J jnl
CoRR
Weijiang Lai, Beihong Jin, Di Zhang, Siru Chen, Jiongyan Zhang, Yuhang Gou, Jian Dong, Xingxing Wang
2025 A conf
RecSys
Weijiang Lai, Beihong Jin, Jiongyan Zhang, Yiyuan Zheng, Jian Dong, Jia Cheng, Jun Lei, Xingxing Wang
2025 J jnl
CoRR
Weijiang Lai, Beihong Jin, Jiongyan Zhang, Yiyuan Zheng, Jian Dong, Jia Cheng, Jun Lei, Xingxing Wang
2025 A conf
RecSys
Weijiang Lai, Beihong Jin, Yapeng Zhang, Yiyuan Zheng, Rui Zhao, Jian Dong, Jun Lei, Xingxing Wang
2025 J jnl
CoRR
Weijiang Lai, Beihong Jin, Yapeng Zhang, Yiyuan Zheng, Rui Zhao, Jian Dong, Jun Lei, Xingxing Wang
2024 J jnl
CoRR
Weijiang Lai, Beihong Jin, Beibei Li, Yiyuan Zheng, Rui Zhao
2024 conf
ECML/PKDD (9)
Yiyuan Zheng, Beibei Li, Beihong Jin, Rui Zhao, Weijiang Lai, Tao Xiang
2024 conf
ECML/PKDD (9)
Rui Zhao, Beihong Jin, Yimin Lv, Yiyuan Zheng, Weijiang Lai
2024 conf
DASFAA (3)
Yiyuan Zheng, Beihong Jin, Beibei Li, Weijiang Lai, Tao Xiang
2023 conf
ECML/PKDD (6)
Weijiang Lai, Beihong Jin, Beibei Li, Yiyuan Zheng, Rui Zhao
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