def visit_float_is_subnormal(self, e):
arg = e.arg(0)
self._check_fp_sort(arg)
arg_sort = e.arg(0).sort()
smallest_positive_normal = self._get_smallest_positive_normal_for(
arg_sort)
largest_negative_normal = self._get_largest_negative_normal_for(
arg_sort)
temp = z3.Or(
z3.And(z3.fpLT(arg, smallest_positive_normal),
z3.fpGT(arg, z3.fpPlusZero(arg_sort))),
z3.And(z3.fpGT(arg, largest_negative_normal),
z3.fpLT(arg, z3.fpMinusZero(arg_sort))))
self.visit(temp)
def visit_float_is_negative(self, e):
arg = e.arg(0)
self._check_fp_sort(arg)
arg_sort = e.arg(0).sort()
zero = None
# FIXME: This isn't sound. We can't distinguish +0 and -0
# in Coral's constraint language
self._unsound_translation('fp.isNegative')
if self._is_float32_sort(arg_sort):
zero = z3.fpPlusZero(z3.Float32())
elif self._is_float64_sort(arg_sort):
zero = z3.fpPlusZero(z3.Float64())
else:
raise CoralPrinterException('Unhandled fp.isNegative case')
tmp = z3.fpLT(arg, zero)
self.visit(tmp)
def _op_raw_fpLT(self, a, b):
return z3.fpLT(a, b, ctx=self._context)
def _op_raw_fpLT(self, a, b):
return z3.fpLT(a, b, ctx=self._context)
class BaseSMTTranslator():
__metaclass__ = MetaTranslator
def __init__(self, type_model):
self.types = type_model
self.fresh = 0
self.defs = [] # current defined-ness conditions
self.nops = [] # current non-poison conditions
self.qvars = []
self.attrs = collections.defaultdict(dict)
# term -> attr -> var
def eval(self, term):
'''smt.eval(term) -> Z3 expression
Translate the term (and subterms), adding its definedness conditons,
nonpoison conditions, and quantifier variables to the state.
'''
logger.debug('eval %s', term)
return eval(term, self)
def __call__(self, term):
'''smt(term) -> Z3 expression, def conds, nonpoison conds, qvars
Clear the current state, translate the term (and subterms), and
return the translation, definedness conditions, nonpoison conditions,
and quantified variables.
Quantified variables are guaranteed to be unique between different
calls to the same SMTTranslator object.
'''
logger.debug('call %s', term)
self.defs = []
self.nops = []
self.qvars = []
v = eval(term, self)
return v, self.defs, self.nops, self.qvars
def add_defs(self, *defs):
self.defs += defs
def add_nops(self, *nops):
self.nops += nops
def add_qvar(self, *qvars):
self.qvars += qvars
def type(self, term):
return self.types[term]
def fresh_bool(self):
self.fresh += 1
return z3.Bool('ana_' + str(self.fresh))
def fresh_var(self, ty, prefix='undef_'):
self.fresh += 1
return z3.Const(prefix + str(self.fresh), _ty_sort(ty))
def _conditional_value(self, conds, v, name=''):
raise NotImplementedError
def _conditional_conv_value(self, conds, v, name=''):
raise NotImplementedError
def _binary_operator(self, term, op, defined, poisons):
x = self.eval(term.x)
y = self.eval(term.y)
if defined:
self.add_defs(*defined(x, y))
if poisons:
for f in poisons:
if f in self.attrs[term]:
self.add_nops(
z3.Implies(self.attrs[term][f], poisons[f](x, y)))
elif f in term.flags:
self.add_nops(poisons[f](x, y))
return op(x, y)
def _float_binary_operator(self, term, op):
logger.debug('_fbo: %s\n%s', term, self.attrs[term])
x = self.eval(term.x)
y = self.eval(term.y)
z = op(x, y)
conds = []
if 'nnan' in self.attrs[term]:
df = z3.And(z3.Not(z3.fpIsNaN(x)), z3.Not(z3.fpIsNaN(y)),
z3.Not(z3.fpIsNaN(z)))
conds.append(z3.Implies(self.attrs[term]['nnan'], df))
elif 'nnan' in term.flags:
conds += [
z3.Not(z3.fpIsNaN(x)),
z3.Not(z3.fpIsNaN(y)),
z3.Not(z3.fpIsNaN(z))
]
if 'ninf' in self.attrs[term]:
df = z3.And(z3.Not(z3.fpIsInf(x)), z3.Not(z3.fpIsInf(y)),
z3.Not(z3.fpIsInf(z)))
conds.append(z3.Implies(self.attrs[term]['ninf'], df))
elif 'ninf' in term.flags:
conds += [
z3.Not(z3.fpIsInf(x)),
z3.Not(z3.fpIsInf(y)),
z3.Not(z3.fpIsInf(z))
]
if 'nsz' in self.attrs[term] or 'nsz' in term.flags:
# NOTE: this will return a different qvar for each (in)direct reference
# to this term. Is this desirable?
b = self.fresh_bool()
self.add_qvar(b)
z = op(x, y)
c = z3.fpIsZero(z)
if 'nsz' in self.attrs[term]:
c = z3.And(self.attrs[term]['nsz'], c)
s = _ty_sort(self.type(term))
z = z3.If(c, z3.If(b, 0, z3.fpMinusZero(s)), z)
if isinstance(term, FDivInst):
c = [z3.Not(z3.fpIsZero(x)), z3.fpIsZero(y)]
if 'nsz' in self.attrs[term]:
c.append(self.attrs[term]['nsz'])
z = z3.If(
z3.And(c),
z3.If(b, z3.fpPlusInfinity(s), z3.fpMinusInfinity(s)), z)
return self._conditional_value(conds, z, term.name)
_icmp_ops = {
'eq': operator.eq,
'ne': operator.ne,
'ugt': z3.UGT,
'uge': z3.UGE,
'ult': z3.ULT,
'ule': z3.ULE,
'sgt': operator.gt,
'sge': operator.ge,
'slt': operator.lt,
'sle': operator.le,
}
_fcmp_ops = {
'false': lambda x, y: z3.BoolVal(False),
'oeq': z3.fpEQ,
'ogt': z3.fpGT,
'oge': z3.fpGEQ,
'olt': z3.fpLT,
'ole': z3.fpLEQ,
'one': lambda x, y: z3.Not(fpUEQ(x, y)),
'ord': lambda x, y: z3.Not(z3.Or(z3.fpIsNaN(x), z3.fpIsNaN(y))),
'ueq': fpUEQ,
'ugt': lambda x, y: z3.Not(z3.fpLEQ(x, y)),
'uge': lambda x, y: z3.Not(z3.fpLT(x, y)),
'ult': lambda x, y: z3.Not(z3.fpGEQ(x, y)),
'ule': lambda x, y: z3.Not(z3.fpGT(x, y)),
'une': z3.fpNEQ,
'uno': lambda x, y: z3.Or(z3.fpIsNaN(x), z3.fpIsNaN(y)),
'true': lambda x, y: z3.BoolVal(True),
}
def _must_analysis(self, term, op):
args = (self.eval(a) for a in term._args)
if all(isinstance(a, Constant) for a in term._args):
return op(*args)
c = self.fresh_bool()
self.add_defs(z3.Implies(c, op(*args)))
return c
def _has_attr(self, attr, term):
if attr in term.flags:
return z3.BoolVal(True)
return self._get_attr_var(attr, term)
def _get_attr_var(self, attr, term):
if attr in self.attrs[term]:
return self.attrs[term][attr]
# TODO: pick name better
b = self.fresh_bool()
logger.debug('Creating attr var %s for %s:%s', b, term, attr)
self.attrs[term][attr] = b
return b
class BaseSMTEncoder():
__metaclass__ = MetaEncoder
def __init__(self, type_model):
self.types = type_model
self.fresh = 0
self.reset()
self._analysis = collections.defaultdict(dict)
# name -> key -> var
def reset(self):
self.defs = [] # current defined-ness conditions
self.nops = [] # current non-poison conditions
self._safe = [] # current safety conditions
self._aux = [] # current auxiliary conditions
self.qvars = []
def eval(self, term):
"""Return the SMT translation of the term. Any side conditions are added
to the translator context.
"""
logger.debug('eval %s', term)
return eval(term, self)
def __call__(self, term):
"""Interpret the term in a fresh translator context.
Quantified variables are guaranteed to be unique between different
calls to the same SMTTranslator object.
"""
# WARNING: calling eval after __call__ will modify the Interp
# returned by __call__. Maybe better to clear everything after calling
# eval? Perhaps best to clear both, but that wastes effort.
logger.debug('call %s', term)
self.reset()
v = eval(term, self)
return Interp(
value = v,
defined = self.defs,
nonpoison = self.nops,
safe = self._safe,
aux = self._aux,
qvars = self.qvars,
)
def _conjunction(self, clauses):
context = []
for c in clauses:
with self.local_safe() as s:
p = self.eval(c)
self.add_safe(*mk_implies(context, s))
context.append(p)
return context
def conjunction(self, clauses):
"""Interpret a list of predicates in a fresh context.
The Interp.value returned will be a list of SMT expressions.
"""
self.reset()
ps = self._conjunction(clauses)
return Interp(
value = ps,
defined = self.defs,
nonpoison = self.nops,
safe = self._safe,
aux = self._aux,
qvars = self.qvars,
)
def add_defs(self, *defs):
"""Add well-defined conditions to the current translator context.
"""
self.defs += defs
@contextmanager
def local_defined(self):
"""Create a context with well-defined conditions independent from any prior
conditions.
Returns the list of well-defined conditions associated with the operations
in the context.
Usage:
with smt.local_defined() as s:
<operations>
"""
old = self.defs
try:
new = []
self.defs = new
yield new
finally:
self.defs = old
def add_nonpoison(self, *nonpoisons):
"""Add non-poison conditions to current translator context.
"""
self.nops += nonpoisons
add_nops = add_nonpoison # TODO: deprecate
@contextmanager
def local_nonpoison(self):
"""Create a context with nonpoison conditions independent from any prior
conditions.
Returns the list of nonpoison conditions associated with the operations in
the context.
Usage:
with smt.local_nonpoison() as s:
<operations>
"""
old = self.nops
try:
new = []
self.nops = new
yield new
finally:
self.nops = old
def add_safe(self, *safe):
"""Add safety conditions to the current translator context.
"""
self._safe += safe
@contextmanager
def local_safe(self):
"""Create a context with safety conditions independent from any prior
conditions.
Returns the list of safety conditions associated with the operations in
the context.
Usage:
with smt.local_safe() as s:
<operations>
"""
old = self._safe
try:
new = []
self._safe = new
yield new
finally:
self._safe = old
def add_aux(self, *auxs):
"""Add auxiliary conditions to the current translator context.
"""
self._aux += auxs
def add_qvar(self, *qvars):
"""Add quantified variables to the current translator context.
"""
self.qvars += qvars
def type(self, term):
return self.types[term]
def fresh_bool(self):
self.fresh += 1
return z3.Bool('ana_' + str(self.fresh))
def fresh_var(self, ty, prefix='undef_'):
self.fresh += 1
return z3.Const(prefix + str(self.fresh), _ty_sort(ty))
def has_analysis(self, name, key):
return name in self._analysis and key in self._analysis[name]
def get_analysis(self, name, key):
return self._analysis[name][key]
def new_analysis(self, name, key, type=None):
if key in self._analysis[name]:
raise ValueError('Attempt to recreate analysis {} for {}'.format(
name, key))
self.fresh += 1
r = z3.Const(
'ana_{}_{}'.format(name, self.fresh),
z3.BoolSort() if type is None else _ty_sort(type))
self._analysis[name][key] = r
return r
def _conditional_value(self, conds, v, name=''):
raise NotImplementedError('{} does not support floating-point'.format(
type(self).__name__.lower()))
def _conditional_conv_value(self, conds, v, name=''):
raise NotImplementedError(
'{} does not support floating-point conversion'.format(
type(self).__name__.lower()))
def _binary_operator(self, term, op, defined, nonpoison, poisons):
x = self.eval(term.x)
y = self.eval(term.y)
if defined:
self.add_defs(*defined(x,y))
if nonpoison:
self.add_nonpoison(*nonpoison(x,y))
if poisons:
for f in poisons:
try:
b = self.get_analysis(f, term)
self.add_nonpoison(z3.Implies(b, poisons[f](x, y)))
except KeyError:
if f in term.flags:
self.add_nonpoison(poisons[f](x, y))
return op(x,y)
def _float_binary_operator(self, term, op):
x = self.eval(term.x)
y = self.eval(term.y)
z = op(x,y)
conds = []
if self.has_analysis('nnan', term):
df = z3.And(z3.Not(z3.fpIsNaN(x)), z3.Not(z3.fpIsNaN(y)),
z3.Not(z3.fpIsNaN(z)))
conds.append(z3.Implies(self.get_analysis('nnan', term), df))
elif 'nnan' in term.flags:
conds += [z3.Not(z3.fpIsNaN(x)), z3.Not(z3.fpIsNaN(y)),
z3.Not(z3.fpIsNaN(z))]
if self.has_analysis('ninf', term):
df = z3.And(z3.Not(z3.fpIsInf(x)), z3.Not(z3.fpIsInf(y)),
z3.Not(z3.fpIsInf(z)))
conds.append(z3.Implies(self.get_analysis('ninf', term), df))
elif 'ninf' in term.flags:
conds += [z3.Not(z3.fpIsInf(x)), z3.Not(z3.fpIsInf(y)),
z3.Not(z3.fpIsInf(z))]
if self.has_analysis('nsz', term) or 'nsz' in term.flags:
# NOTE: this will return a different qvar for each (in)direct reference
# to this term. Is this desirable?
b = self.fresh_bool()
self.add_qvar(b)
z = op(x,y)
c = z3.fpIsZero(z)
if self.has_analysis('nsz', term):
c = z3.And(self.get_analysis('nsz', term), c)
s = _ty_sort(self.type(term))
z = z3.If(c, z3.If(b, 0, z3.fpMinusZero(s)), z)
if isinstance(term, FDivInst):
c = [z3.Not(z3.fpIsZero(x)), z3.fpIsZero(y)]
if self.has_analysis('nsz', term):
c.append(self.get_analysis('nsw', term))
z = z3.If(z3.And(c),
z3.If(b, z3.fpPlusInfinity(s), z3.fpMinusInfinity(s)),
z)
return self._conditional_value(conds, z, term.name)
_icmp_ops = {
'eq': operator.eq,
'ne': operator.ne,
'ugt': z3.UGT,
'uge': z3.UGE,
'ult': z3.ULT,
'ule': z3.ULE,
'sgt': operator.gt,
'sge': operator.ge,
'slt': operator.lt,
'sle': operator.le,
}
_fcmp_ops = {
'false': lambda x,y: z3.BoolVal(False),
'oeq': z3.fpEQ,
'ogt': z3.fpGT,
'oge': z3.fpGEQ,
'olt': z3.fpLT,
'ole': z3.fpLEQ,
'one': lambda x,y: z3.Not(fpUEQ(x,y)),
'ord': lambda x,y: z3.Not(z3.Or(z3.fpIsNaN(x), z3.fpIsNaN(y))),
'ueq': fpUEQ,
'ugt': lambda x,y: z3.Not(z3.fpLEQ(x,y)),
'uge': lambda x,y: z3.Not(z3.fpLT(x,y)),
'ult': lambda x,y: z3.Not(z3.fpGEQ(x,y)),
'ule': lambda x,y: z3.Not(z3.fpGT(x,y)),
'une': z3.fpNEQ,
'uno': lambda x,y: z3.Or(z3.fpIsNaN(x), z3.fpIsNaN(y)),
'true': lambda x,y: z3.BoolVal(True),
}