def process(self, doAST=False):
logger.debug('METHOD : %s', self.name)
# Native methods... no blocks.
if self.start_block is None:
logger.debug('Native Method.')
if doAST:
self.ast = JSONWriter(None, self).get_ast()
else:
self.writer = Writer(None, self)
self.writer.write_method()
return
# Construct the CFG
graph = construct(self.start_block, self.var_to_name, self.exceptions)
self.graph = graph
if not __debug__:
# TODO: use tempfile to create a correct tempfile (cross platform compatible)
util.create_png(self.cls_name, self.name, graph, '/tmp/dad/blocks')
use_defs, def_uses = build_def_use(graph, self.lparams)
split_variables(graph, self.var_to_name, def_uses, use_defs)
dead_code_elimination(graph, def_uses, use_defs)
register_propagation(graph, def_uses, use_defs)
# FIXME var_to_name need to contain the created tmp variables.
# This seems to be a workaround, we add them into the list manually
for var, i in def_uses:
if not isinstance(var, int):
self.var_to_name[var] = var.upper()
place_declarations(graph, self.var_to_name, def_uses, use_defs)
del def_uses, use_defs
# After the DCE pass, some nodes may be empty, so we can simplify the
# graph to delete these nodes.
# We start by restructuring the graph by spliting the conditional nodes
# into a pre-header and a header part.
split_if_nodes(graph)
# We then simplify the graph by merging multiple statement nodes into
# a single statement node when possible. This also delete empty nodes.
simplify(graph)
graph.compute_rpo()
if not __debug__:
# TODO: use tempfile to create a correct tempfile (cross platform compatible)
util.create_png(self.cls_name, self.name, graph, '/tmp/dad/pre-structured')
identify_structures(graph, graph.immediate_dominators())
if not __debug__:
# TODO: use tempfile to create a correct tempfile (cross platform compatible)
util.create_png(self.cls_name, self.name, graph, '/tmp/dad/structured')
if doAST:
self.ast = JSONWriter(graph, self).get_ast()
else:
self.writer = Writer(graph, self)
self.writer.write_method()
def process(self, doAST=False):
logger.debug('METHOD : %s', self.name)
# Native methods... no blocks.
if self.start_block is None:
logger.debug('Native Method.')
if doAST:
self.ast = JSONWriter(None, self).get_ast()
else:
self.writer = Writer(None, self)
self.writer.write_method()
return
# Construct the CFG
graph = construct(self.start_block, self.var_to_name, self.exceptions)
self.graph = graph
if not __debug__:
# TODO: use tempfile to create a correct tempfile (cross platform compatible)
util.create_png(self.cls_name, self.name, graph, '/tmp/dad/blocks')
use_defs, def_uses = build_def_use(graph, self.lparams)
split_variables(graph, self.var_to_name, def_uses, use_defs)
dead_code_elimination(graph, def_uses, use_defs)
register_propagation(graph, def_uses, use_defs)
# FIXME var_to_name need to contain the created tmp variables.
# This seems to be a workaround, we add them into the list manually
for var, i in def_uses:
if not isinstance(var, int):
self.var_to_name[var] = var.upper()
place_declarations(graph, self.var_to_name, def_uses, use_defs)
del def_uses, use_defs
# After the DCE pass, some nodes may be empty, so we can simplify the
# graph to delete these nodes.
# We start by restructuring the graph by spliting the conditional nodes
# into a pre-header and a header part.
split_if_nodes(graph)
# We then simplify the graph by merging multiple statement nodes into
# a single statement node when possible. This also delete empty nodes.
simplify(graph)
graph.compute_rpo()
if not __debug__:
# TODO: use tempfile to create a correct tempfile (cross platform compatible)
util.create_png(self.cls_name, self.name, graph, '/tmp/dad/pre-structured')
identify_structures(graph, graph.immediate_dominators())
if not __debug__:
# TODO: use tempfile to create a correct tempfile (cross platform compatible)
util.create_png(self.cls_name, self.name, graph, '/tmp/dad/structured')
if doAST:
self.ast = JSONWriter(graph, self).get_ast()
else:
self.writer = Writer(graph, self)
self.writer.write_method()
def process(self, doAST=False):
logger.debug('METHOD : %s', self.name)
# Native methods... no blocks.
if self.start_block is None:
logger.debug('Native Method.')
if doAST:
self.ast = JSONWriter(None, self).get_ast()
else:
self.writer = Writer(None, self)
self.writer.write_method()
return
graph = construct(self.start_block, self.var_to_name, self.exceptions)
self.graph = graph
if not __debug__:
util.create_png(self.cls_name, self.name, graph, '/tmp/dad/blocks')
use_defs, def_uses = build_def_use(graph, self.lparams)
split_variables(graph, self.var_to_name, def_uses, use_defs)
dead_code_elimination(graph, def_uses, use_defs)
register_propagation(graph, def_uses, use_defs)
place_declarations(graph, self.var_to_name, def_uses, use_defs)
del def_uses, use_defs
# After the DCE pass, some nodes may be empty, so we can simplify the
# graph to delete these nodes.
# We start by restructuring the graph by spliting the conditional nodes
# into a pre-header and a header part.
split_if_nodes(graph)
# We then simplify the graph by merging multiple statement nodes into
# a single statement node when possible. This also delete empty nodes.
simplify(graph)
graph.compute_rpo()
if not __debug__:
util.create_png(self.cls_name, self.name, graph,
'/tmp/dad/pre-structured')
identify_structures(graph, graph.immediate_dominators())
if not __debug__:
util.create_png(self.cls_name, self.name, graph,
'/tmp/dad/structured')
if doAST:
self.ast = JSONWriter(graph, self).get_ast()
else:
self.writer = Writer(graph, self)
self.writer.write_method()
def process(self, doAST=False):
logger.debug('METHOD : %s', self.name)
# Native methods... no blocks.
if self.start_block is None:
logger.debug('Native Method.')
if doAST:
self.ast = JSONWriter(None, self).get_ast()
else:
self.writer = Writer(None, self)
self.writer.write_method()
return
graph = construct(self.start_block, self.var_to_name, self.exceptions)
self.graph = graph
if not __debug__:
util.create_png(self.cls_name, self.name, graph, '/tmp/dad/blocks')
use_defs, def_uses = build_def_use(graph, self.lparams)
split_variables(graph, self.var_to_name, def_uses, use_defs)
dead_code_elimination(graph, def_uses, use_defs)
register_propagation(graph, def_uses, use_defs)
place_declarations(graph, self.var_to_name, def_uses, use_defs)
del def_uses, use_defs
# After the DCE pass, some nodes may be empty, so we can simplify the
# graph to delete these nodes.
# We start by restructuring the graph by spliting the conditional nodes
# into a pre-header and a header part.
split_if_nodes(graph)
# We then simplify the graph by merging multiple statement nodes into
# a single statement node when possible. This also delete empty nodes.
simplify(graph)
graph.compute_rpo()
if not __debug__:
util.create_png(self.cls_name, self.name, graph,
'/tmp/dad/pre-structured')
identify_structures(graph, graph.immediate_dominators())
if not __debug__:
util.create_png(self.cls_name, self.name, graph,
'/tmp/dad/structured')
if doAST:
self.ast = JSONWriter(graph, self).get_ast()
else:
self.writer = Writer(graph, self)
self.writer.write_method()
def process(self, doAST=False):
"""
Processes the method and decompile the code.
There are two modes of operation:
1) Normal Decompilation to Java Code
2) Decompilation into an abstract syntax tree (AST)
The Decompilation is done twice. First, a rough decompilation is created,
which is then optimized. Second, the optimized version is used to create the final version.
:param doAST: generate AST instead of Java Code
"""
logger.debug('METHOD : %s', self.name)
# Native methods... no blocks.
if self.start_block is None:
logger.debug('Native Method.')
if doAST:
self.ast = JSONWriter(None, self).get_ast()
else:
self.writer = Writer(None, self)
self.writer.write_method()
return
# Construct the CFG
graph = construct(self.start_block, self.var_to_name, self.exceptions)
self.graph = graph
if not __debug__:
# TODO: use tempfile to create a correct tempfile (cross platform compatible)
util.create_png(self.cls_name, self.name, graph, '/tmp/dad/blocks')
use_defs, def_uses = build_def_use(graph, self.lparams)
split_variables(graph, self.var_to_name, def_uses, use_defs)
dead_code_elimination(graph, def_uses, use_defs)
register_propagation(graph, def_uses, use_defs)
resolve_variables_type(graph, self.var_to_name, def_uses, use_defs)
new_instance_propgation(graph, def_uses, use_defs) #for dummy
setattr(graph, "group_var",
group_variables(self.var_to_name, def_uses, use_defs))
# FIXME var_to_name need to contain the created tmp variables.
# This seems to be a workaround, we add them into the list manually
for var, i in def_uses:
if not isinstance(var, int):
self.var_to_name[var] = var.upper()
place_declarations(graph, self.var_to_name, def_uses, use_defs)
del def_uses, use_defs
# After the DCE pass, some nodes may be empty, so we can simplify the
# graph to delete these nodes.
# We start by restructuring the graph by spliting the conditional nodes
# into a pre-header and a header part.
split_if_nodes(graph)
# We then simplify the graph by merging multiple statement nodes into
# a single statement node when possible. This also delete empty nodes.
simplify(graph)
graph.compute_rpo()
if not __debug__:
# TODO: use tempfile to create a correct tempfile (cross platform compatible)
util.create_png(self.cls_name, self.name, graph,
'/tmp/dad/pre-structured')
identify_structures(graph, graph.immediate_dominators())
if not __debug__:
# TODO: use tempfile to create a correct tempfile (cross platform compatible)
util.create_png(self.cls_name, self.name, graph,
'/tmp/dad/structured')
if doAST:
self.ast = JSONWriter(graph, self).get_ast()
else:
self.writer = Writer(graph, self)
self.writer.write_method()