Halim Zeghdoudi

13 papers Journal 13
YearRankTypeTitle / Venue / Authors
2026 J jnl
Astron. Comput.
Abdelfateh Beghriche, Zineb Azouz, Halim Zeghdoudi
2026 J jnl
J. Comput. Appl. Math.
Halim Zeghdoudi, Mohamed Amine Kerker, Elif Boduroglu
2026 J jnl
J. Comput. Appl. Math.
Halim Zeghdoudi, Zoheir Chebel, Chaabane Benatmane
2025 J jnl
Comput.
Halim Zeghdoudi, Sandra S. Ferreira, Vinoth Raman, Dário Ferreira
2024 J jnl
Int. J. Comput. Sci. Sport
Allaeddine Haddari, Halim Zeghdoudi, Vinoth Raman
2023 J jnl
IEEE Access
Nawel Khodja, Ahmed M. Gemeay, Halim Zeghdoudi, Kadir Karakaya, Arwa M. Alshangiti, Mahmoud Ebrahim Bakr, Oluwafemi Samson Balogun, Abdisalam Hassan Muse, Eslam Hussam
2023 J jnl
Frontiers Appl. Math. Stat.
Moulouk Halima Benchettah, Halim Zeghdoudi, Vinoth Raman
2023 J jnl
IEEE Access
Abdelfateh Beghriche, Yusra A. Tashkandy, Mahmoud Ebrahim Bakr, Halim Zeghdoudi, Ahmed M. Gemeay, Md. Moyazzem Hossain, Abdisalam Hassan Muse
2022 J jnl
Oper. Res. Decis.
Farouk Metiri, Halim Zeghdoudi, Abdelali Ezzebsa
2020 J jnl
Int. J. Control
Mimia Benhadri, Tomás Caraballo, Halim Zeghdoudi
2018 J jnl
J. Stat. Theory Appl.
Fatma Zohra Attoui, Halim Zeghdoudi, Ahmed Saadoun
2018 J jnl
Int. J. Comput. Sci. Math.
Hamouda Messaadia, Halim Zeghdoudi
2016 J jnl
J. Comput. Appl. Math.
Sihem Nedjar, Halim Zeghdoudi
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