J. Duncan Whyatt

14 papers Journal 13Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
Environ. Model. Softw.
Josep Serra Gallego, Hollie Blaydes, Emma Gardner, Richard F. Pywell, J. Duncan Whyatt, John W. Redhead
2023 J jnl
Int. J. Geogr. Inf. Sci.
Jonathan J. Huck, J. Duncan Whyatt, Gemma Davies, John Dixon, Brendan Sturgeon, Bree Hocking, Colin Tredoux, Neil Jarman, Dominic Bryan
2019 J jnl
Remote. Sens.
Taher M. Radwan, George Alan Blackburn, J. Duncan Whyatt, Peter M. Atkinson
2019 J jnl
Comput. Environ. Urban Syst.
David Gullick, George Alan Blackburn, J. Duncan Whyatt, Petr Vopenka, Jon Murray, J. Abbatt
2016 J jnl
Int. J. Appl. Earth Obs. Geoinformation
Ahmed K. Nassar, George Alan Blackburn, J. Duncan Whyatt
2015 J jnl
J. Spatial Inf. Sci.
Jonny Huck, J. Duncan Whyatt, Paul Coulton
2014 J jnl
Comput. Environ. Urban Syst.
Ahmed K. Nassar, George Alan Blackburn, J. Duncan Whyatt
2013 J jnl
Trans. GIS
Amy Fowler, J. Duncan Whyatt, Gemma Davies, Rebecca Ellis
2010 J jnl
Trans. GIS
Emma J. S. Ferranti, J. Duncan Whyatt, Roger J. Timmis, Gemma Davies
2009 J jnl
Trans. GIS
Gemma Davies, J. Duncan Whyatt
2008 conf
Mobile HCI
William Bamford, Paul Coulton, Marion Walker, J. Duncan Whyatt, Gemma Davies, Colin Pooley
1991 J jnl
Softw. Pract. Exp.
Jonathan R. Vaughan, J. Duncan Whyatt, Graham R. Brookes
1991 J jnl
Comput. Graph. Forum
Mahes Visvalingam, J. Duncan Whyatt
1990 J jnl
Comput. Graph. Forum
Mahes Visvalingam, J. Duncan Whyatt
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