Carsten Moldenhauer

14 papers A* 3A 1B 1Journal 5Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
CoRR
Carsten Moldenhauer, Philipp Germann, Cedric Heimhofer, Caroline Spieckermann, Andreas Andresen
2016 conf
SWAT
Jaroslaw Byrka, Mateusz Lewandowski, Carsten Moldenhauer
2016 J jnl
CoRR
Jaroslaw Byrka, Mateusz Lewandowski, Carsten Moldenhauer
2015 A* conf
SODA
Marco Di Summa, Friedrich Eisenbrand, Yuri Faenza, Carsten Moldenhauer
2014 J jnl
CoRR
Marco Di Summa, Friedrich Eisenbrand, Yuri Faenza, Carsten Moldenhauer
2014 conf
FSTTCS
Adrian Bock, Yuri Faenza, Carsten Moldenhauer, Andres J. Ruiz-Vargas
2013 J jnl
Inf. Comput.
Carsten Moldenhauer
2011 A conf
STACS
Antonios Antoniadis, Falk Hüffner, Pascal Lenzner, Carsten Moldenhauer, Alexander Souza
2011 conf
ICALP (1)
Carsten Moldenhauer
2010 J jnl
CoRR
Antonios Antoniadis, Falk Hüffner, Pascal Lenzner, Carsten Moldenhauer, Alexander Souza
2010 A* conf
AAAI
Ariel Felner, Carsten Moldenhauer, Nathan R. Sturtevant, Jonathan Schaeffer
2010 B conf
SOCS
Carsten Moldenhauer, Ariel Felner, Nathan R. Sturtevant, Jonathan Schaeffer
2009 A* conf
IJCAI
Carsten Moldenhauer, Nathan R. Sturtevant
2009 conf
AAMAS (2)
Carsten Moldenhauer, Nathan R. Sturtevant
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