miasm2.expression.expression_helper.ExprRandom Class Reference

Inheritance diagram for miasm2.expression.expression_helper.ExprRandom:

Collaboration diagram for miasm2.expression.expression_helper.ExprRandom:

Public Member Functions
def	identifier
def	number
def	atomic
def	operation
def	slice
def	compose
def	memory
def	get

Static Public Attributes
int	identifier_len = 5
	identifier_charset = string.letters
int	number_max = 0xFFFFFFFF
dictionary	operations_by_args_number
int	operations_max_args_number = 5
	perfect_tree = True
int	slice_add_size = 10
int	compose_max_layer = 5
int	memory_max_address_size = 32
	reuse_element = True
dictionary	generated_elements = {}

Private Member Functions
def	_gen

Detailed Description

Return an expression randomly generated

Definition at line 368 of file expression_helper.py.

Member Function Documentation

def miasm2.expression.expression_helper.ExprRandom._gen (   cls,   size = 32,   depth = 1  )

private

Internal function for generating sub-expression according to options
@size: (optional) Operation size
@depth: (optional) Expression depth
/!\ @generated_elements is left modified

Definition at line 488 of file expression_helper.py.

    def _gen(cls, size=32, depth=1):
        """Internal function for generating sub-expression according to options
        @size: (optional) Operation size
        @depth: (optional) Expression depth
        /!\ @generated_elements is left modified
        """
        # Perfect tree handling
        if not cls.perfect_tree:
            depth = random.randint(max(0, depth - 2), depth)

        # Element re-use
        if cls.reuse_element and random.choice([True, False]) and \
                (depth, size) in cls.generated_elements:
            return random.choice(cls.generated_elements[(depth, size)])

        # Recursion stop
        if depth == 0:
            return cls.atomic(size=size)

        # Build a more complex expression
        available_funcs = [cls.operation, cls.slice, cls.compose, cls.memory]
        gen = random.choice(available_funcs)(size=size, depth=depth)

        # Save it
        new_value = cls.generated_elements.get((depth, size), []) + [gen]
        cls.generated_elements[(depth, size)] = new_value
        return gen