def __init__(self): self.result = dict() self.result["bool"] = NamedType("bool") self.combiners = defaultdict(UserFunction) self.current_global_declarations = dict() self.max_recompute = 1 # max number of use to be lazy ModuleAnalysis.__init__(self, StrictAliases, LazynessAnalysis) self.curr_locals_declaration = None
def __init__(self): """ Create empty result graph and gather global declarations. """ self.result = nx.DiGraph() self.current_function = None self.naming = dict() # variable to dependencies for current function. # variable to dependencies for current conditional statement self.in_cond = dict() ModuleAnalysis.__init__(self, GlobalDeclarations)
def __init__(self): class TypeResult(dict): def __init__(self): self.builder = TypeBuilder() def copy(self): other = TypeResult() other.update(self.items()) other.builder = self.builder return other self.result = TypeResult() self.builder = self.result.builder self.result["bool"] = self.builder.NamedType("bool") self.combiners = defaultdict(UserFunction) self.current_global_declarations = dict() self.max_recompute = 1 # max number of use to be lazy ModuleAnalysis.__init__(self, StrictAliases, LazynessAnalysis) self.curr_locals_declaration = None
def __init__(self): class TypeResult(dict): def __init__(self): self.builder = TypeBuilder() def copy(self): other = TypeResult() other.update(self.items()) other.builder = self.builder return other self.result = TypeResult() self.builder = self.result.builder self.result["bool"] = self.builder.NamedType("bool") self.combiners = defaultdict(UserFunction) self.current_global_declarations = dict() self.max_recompute = 1 # max number of use to be lazy ModuleAnalysis.__init__(self, Reorder, StrictAliases, LazynessAnalysis, Immediates) self.curr_locals_declaration = None
def __init__(self): self.result = None self.update = False self.functions = set() ModuleAnalysis.__init__(self, StrictAliases)
def run(self, node, ctx): ModuleAnalysis.run(self, node, ctx) for fun in self.result: for i in xrange(len(fun.read_effects)): self.recursive_weight(fun, i, set()) return {f.func: f.read_effects for f in self.result}
def run(self, node, ctx): ModuleAnalysis.run(self, node, ctx) for fun in self.result: for i in range(len(fun.read_effects)): self.recursive_weight(fun, i, set()) return {f.func: f.read_effects for f in self.result}
def __init__(self): self.result = nx.DiGraph() self.current_function = None ModuleAnalysis.__init__(self, GlobalDeclarations)
def __init__(self): self.result = None self.update = False self.inassert = False self.functions = set() ModuleAnalysis.__init__(self, StrictAliases, ArgumentEffects)