Navve Wasserman

13 papers A* 2Journal 10Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
NeuroImage
Navve Wasserman, Roman Beliy, Roy Urbach, Michal Irani
2025 J jnl
CoRR
Roman Beliy, Amit Zalcher, Jonathan Kogman, Navve Wasserman, Michal Irani
2025 J jnl
CoRR
Navve Wasserman, Matias Cosarinsky, Yuval Golbari, Aude Oliva, Antonio Torralba, Tamar Rott Shaham, Michal Irani
2025 A* conf
EMNLP
Navve Wasserman, Oliver Heinimann, Yuval Golbari, Tal Zimbalist, Eli Schwartz, Michal Irani
2025 J jnl
CoRR
Navve Wasserman, Oliver Heinimann, Yuval Golbari, Tal Zimbalist, Eli Schwartz, Michal Irani
2025 J jnl
CoRR
Amit Zalcher, Navve Wasserman, Roman Beliy, Oliver Heinimann, Michal Irani
2025 J jnl
Trans. Mach. Learn. Res.
Amit Zalcher, Navve Wasserman, Roman Beliy, Oliver Heinimann, Michal Irani
2025 J jnl
CoRR
Yuval Golbari, Navve Wasserman, Gal Vardi, Michal Irani
2025 A* conf
CVPR
Navve Wasserman, Noam Rotstein, Roy Ganz, Ron Kimmel
2025 conf
ACL (1)
Navve Wasserman, Roi Pony, Oshri Naparstek, Adi Raz Goldfarb, Eli Schwartz, Udi Barzelay, Leonid Karlinsky
2025 J jnl
CoRR
Navve Wasserman, Roi Pony, Oshri Naparstek, Adi Raz Goldfarb, Eli Schwartz, Udi Barzelay, Leonid Karlinsky
2024 J jnl
CoRR
Navve Wasserman, Noam Rotstein, Roy Ganz, Ron Kimmel
2024 J jnl
CoRR
Roman Beliy, Navve Wasserman, Amit Zalcher, Michal Irani
redb/extractors/decompiler/bninja/analysis/low_level_normalization.py
← Index redb/extractors/decompiler/bninja/analysis/low_level_normalization.py python
from binaryninja import (
    ILRegister, ILRegisterStack, ILFlag,
    ILIntrinsic, ILSemanticFlagGroup,
)

class LowLevelNormalization:
    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 hasattr(op, "operation"):
                self._collect_ops(op, ops)
            elif isinstance(op, (list, tuple)):
                for sub in op:
                    if hasattr(sub, "operation"):
                        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, ILRegister):
            return "REG"
        if isinstance(val, ILRegisterStack):
            return "REG_STACK"
        if isinstance(val, ILFlag):
            return "FLAG"
        if isinstance(val, ILSemanticFlagGroup):
            return "FLAG_GROUP"
        if isinstance(val, ILIntrinsic):
            return "INTRINSIC"
        if isinstance(val, bool):
            return "BOOL"
        if isinstance(val, int):
            return "CONST"
        return type(val).__name__.upper()

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

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