def compile_assign(self):
code = []
local_syms = []
with ExprContext(code, local_syms):
if isinstance(self.args[0], ivy_ast.Tuple):
args = [sortify_with_inference(a) for a in self.args]
if not isinstance(args[1], ivy_ast.Tuple) or len(
args[0].args) != len(args[1].args):
raise IvyError(self, "wrong number of values in assignment")
for lhs, rhs in zip(args[0].args, args[1].args):
code.append(AssignAction(lhs, rhs))
else:
with top_sort_as_default():
args = [a.compile() for a in self.args]
if isinstance(args[1], ivy_ast.Tuple):
raise IvyError(self, "wrong number of values in assignment")
with ASTContext(self):
teq = sort_infer(Equals(*args))
args = list(teq.args)
code.append(AssignAction(*args))
for c in code:
c.lineno = self.lineno
if len(code) == 1:
return code[0]
res = LocalAction(*(local_syms + [Sequence(*code)]))
res.lineno = self.lineno
return res
def extract(self):
for c in self.code:
c.lineno = self.lineno
if len(self.code) == 1:
return self.code[0]
res = LocalAction(*(self.local_syms + [Sequence(*self.code)]))
res.lineno = self.lineno
return res
def p_action_action_semi_action(p):
'action : action SEMI action'
if isinstance(p[1], Sequence):
p[0] = p[1]
p[0].args.append(p[3])
else:
p[0] = Sequence(p[1], p[3])
p[0].lineno = p[1].lineno
def p_sequence_lcb_actseq_rcb(p):
'sequence : LCB actseq RCB'
stmts = lower_var_stmts(p[2])
if len(stmts) == 1:
p[0] = stmts[0]
else:
p[0] = Sequence(*lower_var_stmts(stmts))
p[0].lineno = get_lineno(p, 1)
def compile_local(self):
sig = ivy_logic.sig.copy()
with sig:
ls = self.args[0:-1]
if len(ls) == 1 and isinstance(ls[0], AssignAction):
v = ls[0]
lhs = v.args[0]
rhs = v.args[1]
# temporarily rename lhs symbol in case it clashes with an existing symbol
# tmp_lhs = lhs.prefix('__var_tmp:')
tmp_lhs = lhs
code = []
local_syms = []
with ExprContext(code, local_syms):
with alpha_sort_as_default():
sym = compile_const(tmp_lhs, sig)
ctmp_lhs = tmp_lhs.compile()
crhs = rhs.compile()
with ASTContext(self):
teq = sort_infer(Equals(ctmp_lhs, crhs))
clhs, crhs = list(teq.args)
# clhs = clhs.drop_prefix('__var_tmp:')
asgn = v.clone([clhs, crhs])
ivy_logic.remove_symbol(sym)
if clhs.rep.name in sig.symbols:
del sig.symbols[clhs.rep.name] # shadow the existing symbol
ivy_logic.add_symbol(clhs.rep.name, clhs.rep.sort)
body = sortify(self.args[-1])
lines = body.args if isinstance(body, Sequence) else [body]
body = Sequence(*([asgn] + lines))
code.append(LocalAction(clhs.rep, body))
for c in code:
c.lineno = self.lineno
if len(code) == 1:
return code[0]
res = LocalAction(*(local_syms + [Sequence(*code)]))
res.lineno = self.lineno
return res
cls = [compile_const(v, sig) for v in ls]
body = sortify(self.args[-1])
res = LocalAction(*(cls + [body]))
res.lineno = self.lineno
return res
def compile_assign(self):
code = []
local_syms = []
with ExprContext(code,local_syms):
args = [sortify_with_inference(a) for a in self.args]
if isinstance(args[0],ivy_ast.Tuple):
if not isinstance(args[1],ivy_ast.Tuple) or len(args[0].args) != len(args[1].args):
raise IvyError(self,"wrong number of values in assignment");
for lhs,rhs in zip(args[0].args,args[1].args):
code.append(AssignAction(lhs,rhs))
elif isinstance(args[1],ivy_ast.Tuple):
raise IvyError(self,"wrong number of values in assignment");
else:
code.append(AssignAction(*args))
if len(code) == 1:
return code[0]
return LocalAction(*(local_syms + [Sequence(*code)]))
def lower_var_stmts(stmts):
for idx, stmt in enumerate(stmts):
if isinstance(stmt, VarAction):
lhs = stmt.args[0]
rhs = stmt.args[1] if len(stmt.args) > 1 else None
lsym = lhs.prefix('loc:')
subst = {lhs.rep: lsym.rep}
lines = lower_var_stmts(stmts[idx + 1:])
lines = [
subst_prefix_atoms_ast(s, subst, None, None) for s in lines
]
if rhs is not None:
asgn = AssignAction(lsym, rhs)
asgn.lineno = stmt.lineno
else:
asgn = lsym
body = Sequence(*lines)
body.lineno = stmt.lineno
res = LocalAction(*[asgn, body])
res.lineno = body.lineno
return stmts[:idx] + [res]
return stmts
def p_optactiondef(p):
'optactiondef : '
p[0] = Sequence()
def p_optaction(p):
'optaction :'
p[0] = Sequence()
def p_action_lcb_rcb(p):
'action : LCB RCB'
p[0] = Sequence()
p[0].lineno = get_lineno(p, 1)
def l2s_tactic(prover, goals, proof):
mod = im.module
goal = goals[0] # pick up the first proof goal
lineno = goal.lineno
conc = ipr.goal_conc(goal) # get its conclusion
if not isinstance(conc, itm.TemporalModels):
raise iu.IvyError(proof, 'proof goal is not temporal')
model = conc.model.clone([])
fmla = conc.fmla
# Get all the temporal properties from the prover environment as assumptions
# Add all the assumed invariants to the model
assumed_gprops = [
x for x in prover.axioms if not x.explicit and x.temporal
]
model.asms.extend(
[p.clone([p.label, p.formula.args[0]]) for p in assumed_gprops])
# TRICKY: We postpone compiling formulas in the tactic until now, so
# that tactics can introduce their own symbols. But, this means that the
# tactic has to be given an appropriate environment label for any temporal
# operators. Here, we compile the invariants in the tactic, using the given
# label.
assert hasattr(proof, 'labels') and len(proof.labels) == 1
proof_label = proof.labels[0]
# print 'proof label: {}'.format(proof_label)
invars = [
ilg.label_temporal(inv.compile(), proof_label)
for inv in proof.tactic_decls
]
l2s_waiting = lg.Const('l2s_waiting', lg.Boolean)
l2s_frozen = lg.Const('l2s_frozen', lg.Boolean)
l2s_saved = lg.Const('l2s_saved', lg.Boolean)
l2s_d = lambda sort: lg.Const('l2s_d', lg.FunctionSort(sort, lg.Boolean))
l2s_a = lambda sort: lg.Const('l2s_a', lg.FunctionSort(sort, lg.Boolean))
l2s_w = lambda vs, t: lg.NamedBinder('l2s_w', vs, proof_label, t)
l2s_s = lambda vs, t: lg.NamedBinder('l2s_s', vs, proof_label, t)
l2s_g = lambda vs, t, environ: lg.NamedBinder('l2s_g', vs, environ, t)
old_l2s_g = lambda vs, t, environ: lg.NamedBinder('_old_l2s_g', vs,
environ, t)
# Desugar the invariants.
#
# $was. phi(V) --> l2s_saved & ($l2s_s V.phi(V))(V)
# $happened. phi --> l2s_saved & ~($l2s_w V.phi(V))(V)
#
# We push $l2s_s inside propositional connectives, so that the saved
# values correspond to atoms. Otherwise, we would have redundant
# saved values, for example p(X) and ~p(X).
def desugar(expr):
def apply_was(expr):
if isinstance(expr, (lg.And, lg.Or, lg.Not, lg.Implies, lg.Iff)):
return expr.clone([apply_was(a) for a in expr.args])
vs = list(iu.unique(ilu.variables_ast(expr)))
return l2s_s(vs, expr)(*vs)
def apply_happened(expr):
vs = list(iu.unique(ilu.variables_ast(expr)))
return lg.Not(l2s_w(vs, expr)(*vs))
if ilg.is_named_binder(expr):
if expr.name == 'was':
if len(expr.variables) > 0:
raise iu.IvyError(
expr, "operator 'was' does not take parameters")
return lg.And(l2s_saved, apply_was(expr.body))
elif expr.name == 'happened':
if len(expr.variables) > 0:
raise iu.IvyError(
expr, "operator 'happened' does not take parameters")
return lg.And(l2s_saved, apply_happened(expr.body))
return expr.clone([desugar(a) for a in expr.args])
invars = map(desugar, invars)
# Add the invariant phi to the list. TODO: maybe, if it is a G prop
# invars.append(ipr.clone_goal(goal,[],invar))
# Add the invariant list to the model
model.invars = model.invars + invars
# for inv in invars:
# print inv
# for b in ilu.named_binders_ast(inv):
# print 'orig binder: {} {} {}'.format(b.name,b.environ,b.body)
# model pass helper funciton
def mod_pass(transform):
model.invars = [transform(x) for x in model.invars]
model.asms = [transform(x) for x in model.asms]
# TODO: what about axioms and properties?
newb = []
model.bindings = [
b.clone([transform(b.action)]) for b in model.bindings
]
model.init = transform(model.init)
# We first convert all temporal operators to named binders, so
# it's possible to normalize them. Otherwise we won't have the
# connection betweel (globally p(X)) and (globally p(Y)). Note
# that we replace them even inside named binders.
l2s_gs = set()
def _l2s_g(vs, t, env):
vs = tuple(vs)
res = l2s_g(vs, t, env)
# print 'l2s_gs: {} {} {}'.format(vs,t,env)
l2s_gs.add((vs, t, env))
return res
replace_temporals_by_l2s_g = lambda ast: ilu.replace_temporals_by_named_binder_g_ast(
ast, _l2s_g)
mod_pass(replace_temporals_by_l2s_g)
not_lf = replace_temporals_by_l2s_g(lg.Not(fmla))
if debug.get():
print "=" * 80 + "\nafter replace_temporals_by_named_binder_g_ast" + "\n" * 3
print "=" * 80 + "\nl2s_gs:"
for vs, t, env in sorted(l2s_gs):
print vs, t, env
print "=" * 80 + "\n" * 3
print model
print "=" * 80 + "\n" * 3
# now we normalize all named binders
mod_pass(ilu.normalize_named_binders)
if debug.get():
print "=" * 80 + "\nafter normalize_named_binders" + "\n" * 3
print model
print "=" * 80 + "\n" * 3
# construct the monitor related building blocks
uninterpreted_sorts = [
s for s in ilg.sig.sorts.values()
if type(s) is lg.UninterpretedSort and s.name not in mod.finite_sorts
]
reset_a = [
AssignAction(l2s_a(s)(v),
l2s_d(s)(v)).set_lineno(lineno)
for s in uninterpreted_sorts for v in [lg.Var('X', s)]
]
add_consts_to_d = [
AssignAction(l2s_d(s)(c), lg.true).set_lineno(lineno)
for s in uninterpreted_sorts for c in ilg.sig.symbols.values()
if c.sort == s
]
# TODO: maybe add all ground terms, not just consts (if stratified)
# TODO: add conjectures that constants are in d and a
# figure out which l2s_w and l2s_s are used in conjectures
named_binders_conjs = defaultdict(
list) # dict mapping names to lists of (vars, body)
for b in ilu.named_binders_asts(model.invars):
# print 'binder: {} {} {}'.format(b.name,b.environ,b.body)
named_binders_conjs[b.name].append((b.variables, b.body))
named_binders_conjs = defaultdict(
list, ((k, list(set(v))) for k, v in named_binders_conjs.iteritems()))
to_wait = [
] # list of (variables, term) corresponding to l2s_w in conjectures
to_wait += named_binders_conjs['l2s_w']
to_save = [
] # list of (variables, term) corresponding to l2s_s in conjectures
to_save += named_binders_conjs['l2s_s']
if debug.get():
print "=" * 40 + "\nto_wait:\n"
for vs, t in to_wait:
print vs, t
print list(ilu.variables_ast(t)) == list(vs)
print
print "=" * 40
save_state = [
AssignAction(l2s_s(vs, t)(*vs), t).set_lineno(lineno)
for vs, t in to_save
]
done_waiting = [forall(vs, lg.Not(l2s_w(vs, t)(*vs))) for vs, t in to_wait]
reset_w = [
AssignAction(
l2s_w(vs, t)(*vs),
lg.And(*([
l2s_d(v.sort)(v)
for v in vs if v.sort.name not in mod.finite_sorts
] + [
lg.Not(t),
replace_temporals_by_l2s_g(
lg.Not(lg.Globally(proof_label, ilu.negate(t))))
]))).set_lineno(lineno) for vs, t in to_wait
]
fair_cycle = [l2s_saved]
fair_cycle += done_waiting
# projection of relations
fair_cycle += [
lg.ForAll(
vs,
lg.Implies(
lg.And(*(l2s_a(v.sort)(v) for v in vs
if v.sort.name not in mod.finite_sorts)),
lg.Iff(l2s_s(vs, t)(
*vs), t))) if len(vs) > 0 else lg.Iff(l2s_s(vs, t), t)
for vs, t in to_save
if (t.sort == lg.Boolean or isinstance(t.sort, lg.FunctionSort)
and t.sort.range == lg.Boolean)
]
# projection of functions and constants
fair_cycle += [
forall(
vs,
lg.Implies(
lg.And(*([
l2s_a(v.sort)(v)
for v in vs if v.sort.name not in mod.finite_sorts
] + ([
lg.Or(l2s_a(t.sort)(l2s_s(vs, t)(*vs)),
l2s_a(t.sort)(t))
] if t.sort.name not in mod.finite_sorts else []))),
lg.Eq(l2s_s(vs, t)(*vs), t))) for vs, t in to_save
if (isinstance(t.sort, lg.UninterpretedSort)
or isinstance(t.sort, lg.FunctionSort)
and isinstance(t.sort.range, lg.UninterpretedSort))
]
assert_no_fair_cycle = AssertAction(lg.Not(
lg.And(*fair_cycle))).set_lineno(lineno)
assert_no_fair_cycle.lineno = goal.lineno
monitor_edge = lambda s1, s2: [
AssumeAction(s1).set_lineno(lineno),
AssignAction(s1, lg.false).set_lineno(lineno),
AssignAction(s2, lg.true).set_lineno(lineno),
]
change_monitor_state = [
ChoiceAction(
# waiting -> frozen
Sequence(
*(monitor_edge(l2s_waiting, l2s_frozen) +
[AssumeAction(x).set_lineno(lineno)
for x in done_waiting] + reset_a)).set_lineno(lineno),
# frozen -> saved
Sequence(*(monitor_edge(l2s_frozen, l2s_saved) + save_state +
reset_w)),
# stay in same state (self edge)
Sequence().set_lineno(lineno),
).set_lineno(lineno)
]
# tableau construction (sort of)
# Note that we first transformed globally and eventually to named
# binders, in order to normalize. Without this, we would get
# multiple redundant axioms like:
# forall X. (globally phi(X)) -> phi(X)
# forall Y. (globally phi(Y)) -> phi(Y)
# and the same redundancy will happen for transition updates.
# temporals = []
# temporals += list(ilu.temporals_asts(
# # TODO: these should be handled by mod_pass instead (and come via l2s_gs):
# # mod.labeled_axioms +
# # mod.labeled_props +
# [lf]
# ))
# temporals += [lg.Globally(lg.Not(t)) for vs, t in to_wait]
# temporals += [lg.Globally(t) for vs, t in l2s_gs]
# # TODO get from temporal axioms and temporal properties as well
# print '='*40 + "\ntemporals:"
# for t in temporals:
# print t, '\n'
# print '='*40
# to_g = [ # list of (variables, formula)
# (tuple(sorted(ilu.variables_ast(tt))), tt) # TODO what about variable normalization??
# for t in temporals
# for tt in [t.body if type(t) is lg.Globally else
# lg.Not(t.body) if type(t) is lg.Eventually else 1/0]
# ]
# TODO: get rid of the above, after properly combining it
to_g = [] # list of (variables, formula)
to_g += list(l2s_gs)
to_g = list(set(to_g))
if debug.get():
print '=' * 40 + "\nto_g:\n"
for vs, t, env in sorted(to_g):
print vs, t, '\n'
print '=' * 40
assume_g_axioms = [
AssumeAction(forall(vs, lg.Implies(l2s_g(vs, t, env)(*vs),
t))).set_lineno(lineno)
for vs, t, env in to_g
]
# now patch the module actions with monitor and tableau
if debug.get():
print "public_actions:", model.calls
# Tableau construction
#
# Each temporal operator has an 'environment'. The operator
# applies to states *not* in actions labeled with this
# environment. This has several consequences:
#
# 1) The operator's semantic constraint is an assumed invariant (i.e.,
# it holds outside of any action)
#
# 2) An 'event' for the temporal operator occurs when (a) we return
# from an execution context inside its environment to one outside,
# or (b) we are outside the environment of the operator and some symbol
# occurring in it's body is mutated.
#
# 3) At any event for the operator, we update its truth value and
# and re-establish its semantic constraint.
#
# This procedure generates code for an event corresponding to a
# list of operators. The tableau state is updated and the
# semantics applied.
def prop_events(gprops):
res = []
for gprop in gprops:
vs, t, env = gprop.variables, gprop.body, gprop.environ
res.append(
AssignAction(
old_l2s_g(vs, t, env)(*vs),
l2s_g(vs, t, env)(*vs)).set_lineno(lineno))
res.append(HavocAction(l2s_g(vs, t, env)(*vs)).set_lineno(lineno))
for gprop in gprops:
vs, t, env = gprop.variables, gprop.body, gprop.environ
res.append(
AssumeAction(
forall(
vs,
lg.Implies(
old_l2s_g(vs, t, env)(*vs),
l2s_g(vs, t, env)(*vs)))).set_lineno(lineno))
res.append(
AssumeAction(
forall(
vs,
lg.Implies(
lg.And(lg.Not(old_l2s_g(vs, t, env)(*vs)), t),
lg.Not(l2s_g(vs, t,
env)(*vs))))).set_lineno(lineno))
res.append(
AssumeAction(forall(vs, lg.Implies(l2s_g(vs, t, env)(*vs),
t))).set_lineno(lineno))
return res
# This procedure generates code for an event corresponding to a
# list of eventualites to be waited on. The tableau state is updated and the
# semantics applied.
def wait_events(waits):
res = []
for wait in waits:
vs = wait.variables
t = wait.body
# (l2s_w V. phi)(V) := (l2s_w V. phi)(V) & ~phi & ~(l2s_g V. ~phi)(V)
res.append(
AssignAction(
wait(*vs),
lg.And(
wait(*vs), lg.Not(t),
replace_temporals_by_l2s_g(
lg.Not(lg.Globally(proof_label, ilu.negate(t)))))
# TODO check this and make sure its correct
# note this adds to l2s_gs
).set_lineno(lineno))
return res
# The following procedure instruments a statement with operator
# events for all of the temporal operators. This depends on the
# statement's environment, that is, current set of environment
# labels.
#
# Currently, the environment labels of a statement have to be
# statically determined, but this could change, i.e., the labels
# could be represented by boolean variables.
#
# First, make some memo tables
envprops = defaultdict(list)
symprops = defaultdict(list)
symwaits = defaultdict(list)
for vs, t, env in l2s_gs:
prop = l2s_g(vs, t, env)
envprops[env].append(prop)
for sym in ilu.symbols_ast(t):
symprops[sym].append(prop)
for vs, t in to_wait:
wait = l2s_w(vs, t)
for sym in ilu.symbols_ast(t):
symwaits[sym].append(wait)
actions = dict((b.name, b.action) for b in model.bindings)
# lines = dict(zip(gprops,gproplines))
def instr_stmt(stmt, labels):
# first, recur on the sub-statements
args = [
instr_stmt(a, labels) if isinstance(a, Action) else a
for a in stmt.args
]
res = stmt.clone(args)
# now add any needed temporal events after this statement
event_props = set()
event_waits = set()
# first, if it is a call, we must consider any events associated with
# the return
# if isinstance(stmt,CallAction):
# callee = actions[stmt.callee()] # get the called action
# exiting = [l for l in callee.labels if l not in labels] # environments we exit on return
# for label in exiting:
# for prop in envprops[label]:
# event_props.add(prop)
# Second, if a symbol is modified, we must add events for every property that
# depends on the symbol, but only if we are not in the environment of that property.
for sym in stmt.modifies():
for prop in symprops[sym]:
# if prop.environ not in labels:
event_props.add(prop)
for wait in symwaits[sym]:
event_waits.add(wait)
# Now, for every property event, we update the property state (none in this case)
# and also assert the property semantic constraint.
events = prop_events(event_props)
events += wait_events(event_waits)
res = iact.postfix_action(res, events)
stmt.copy_formals(res) # HACK: This shouldn't be needed
return res
# Instrument all the actions
model.bindings = [
b.clone([b.action.clone([instr_stmt(b.action.stmt, b.action.labels)])])
for b in model.bindings
]
# Now, for every exported action, we add the l2s construction. On
# exit of each external procedure, we add a tableau event for all
# the operators whose scope is being exited.
#
# TODO: This is wrong in the case of an exported procedure that is
# also internally called. We do *not* want to update the tableau
# in the case of an internal call, since the scope of the
# operators os not exited. One solution to this is to create to
# duplicate the actions so there is one version for internal
# callers and one for external callers. It is possible that this
# is already done by ivy_isolate, but this needs to be verified.
calls = set(model.calls) # the exports
for b in model.bindings:
if b.name in calls:
add_params_to_d = [
AssignAction(l2s_d(p.sort)(p), lg.true)
for p in b.action.inputs if p.sort.name not in mod.finite_sorts
]
# tableau updates for exit to environment
# event_props = set()
# for label in b.action.labels:
# for prop in envprops[label]:
# event_props.add(prop)
# events = prop_events(event_props)
stmt = concat_actions(*(
add_params_to_d +
assume_g_axioms + # could be added to model.asms
[b.action.stmt] + add_consts_to_d)).set_lineno(lineno)
b.action.stmt.copy_formals(stmt) # HACK: This shouldn't be needed
b.action = b.action.clone([stmt])
# The idle action handles automaton state update and cycle checking
idle_action = concat_actions(*(
change_monitor_state +
assume_g_axioms + # could be added to model.asms
add_consts_to_d + [assert_no_fair_cycle])).set_lineno(lineno)
idle_action.formal_params = []
idle_action.formal_returns = []
model.bindings.append(
itm.ActionTermBinding('idle', itm.ActionTerm([], [], [], idle_action)))
model.calls.append('idle')
l2s_init = [
AssignAction(l2s_waiting, lg.true).set_lineno(lineno),
AssignAction(l2s_frozen, lg.false).set_lineno(lineno),
AssignAction(l2s_saved, lg.false).set_lineno(lineno),
]
l2s_init += add_consts_to_d
l2s_init += reset_w
l2s_init += assume_g_axioms
l2s_init += [AssumeAction(not_lf).set_lineno(lineno)]
if not hasattr(model.init, 'lineno'):
model.init.lineno = None # Hack: fix this
model.init = iact.postfix_action(model.init, l2s_init)
if debug.get():
print "=" * 80 + "\nafter patching actions" + "\n" * 3
print model
print "=" * 80 + "\n" * 3
# now replace all named binders by fresh relations
named_binders = defaultdict(
list) # dict mapping names to lists of (vars, body)
for b in ilu.named_binders_asts(
chain(
model.invars,
model.asms,
[model.init],
[b.action for b in model.bindings],
)):
named_binders[b.name].append(b)
named_binders = defaultdict(list, ((k, list(sorted(set(v))))
for k, v in named_binders.iteritems()))
# make sure old_l2s_g is consistent with l2s_g
# assert len(named_binders['l2s_g']) == len(named_binders['_old_l2s_g'])
named_binders['_old_l2s_g'] = [
lg.NamedBinder('_old_l2s_g', b.variables, b.environ, b.body)
for b in named_binders['l2s_g']
]
subs = dict((b, lg.Const('{}_{}'.format(k, i), b.sort))
for k, v in named_binders.iteritems() for i, b in enumerate(v))
if debug.get():
print "=" * 80 + "\nsubs:" + "\n" * 3
for k, v in subs.items():
print k, ' : ', v, '\n'
print "=" * 80 + "\n" * 3
mod_pass(lambda ast: ilu.replace_named_binders_ast(ast, subs))
if debug.get():
print "=" * 80 + "\nafter replace_named_binders" + "\n" * 3
print model
print "=" * 80 + "\n" * 3
# if len(gprops) > 0:
# assumes = [gprop_to_assume(x) for x in gprops]
# model.bindings = [b.clone([prefix_action(b.action,assumes)]) for b in model.bindings]
# HACK: reestablish invariant that shouldn't be needed
for b in model.bindings:
b.action.stmt.formal_params = b.action.inputs
b.action.stmt.formal_returns = b.action.outputs
# Change the conclusion formula to M |= true
conc = itm.TemporalModels(model, lg.And())
# Build the new goal
goal = ipr.clone_goal(goal, ipr.goal_prems(goal), conc)
# Return the new goal stack
goals = [goal] + goals[1:]
return goals
def scenario(self, scen):
init_tokens = set(p.rep for p in scen.args[0].args)
transs_by_action = defaultdict(list)
for tr in scen.args[1:]:
transs_by_action[tr.args[2].args[1].args[0].rep].append(tr)
for (place_name, lineno) in scen.places():
sym = find_symbol(place_name)
iname = place_name + '[init]'
iact = AssignAction(
sym,
ivy_logic.And() if
(place_name in init_tokens) else ivy_logic.Or())
iact.formal_params = []
iact.formal_returns = []
iact.lineno = scen.lineno
self.mod.actions[iname] = iact
self.mixin(
ivy_ast.MixinAfterDef(ivy_ast.Atom(iname),
ivy_ast.Atom('init')))
for actname, trs in transs_by_action.iteritems():
choices = []
params = None
afters = []
for tr in trs:
scmix = tr.args[2]
is_after = isinstance(scmix, ivy_ast.ScenarioAfterMixin)
df = scmix.args[1]
body = compile_action_def(df, self.mod.sig)
seq = []
if not is_after:
for p in tr.args[0].args:
seq.append(AssumeAction(find_symbol(p.rep)))
for p in tr.args[0].args:
seq.append(
AssignAction(find_symbol(p.rep), ivy_logic.Or()))
for p in tr.args[1].args:
seq.append(
AssignAction(find_symbol(p.rep), ivy_logic.And()))
seq.append(body)
seq = Sequence(*seq)
else:
for p in tr.args[0].args:
seq.append(
AssignAction(find_symbol(p.rep), ivy_logic.Or()))
for p in tr.args[1].args:
seq.append(
AssignAction(find_symbol(p.rep), ivy_logic.And()))
seq.append(body)
seq = Sequence(*seq)
seq = IfAction(
And(*[find_symbol(p.rep) for p in tr.args[0].args]),
seq)
if params is None:
params = body.formal_params
returns = body.formal_returns
mixer = scmix.args[0]
mixee = scmix.args[1].args[0]
else:
aparams = df.formal_params + df.formal_returns
subst = dict(zip(aparams, params + returns))
seq = substitute_constants_ast(seq, subst)
seq.lineno = tr.lineno
if not is_after:
choices.append(seq)
else:
afters.append(seq)
if choices:
choice = BalancedChoice(choices)
choice.lineno = choices[0].lineno
choice.formal_params = params
choice.formal_returns = returns
self.mod.actions[mixer.rep] = choice
self.mixin(ivy_ast.MixinBeforeDef(mixer, mixee))
if afters:
choice = Sequence(*afters)
choice.lineno = afters[0].lineno
choice.formal_params = params
choice.formal_returns = returns
self.mod.actions[mixer.rep] = choice
self.mixin(ivy_ast.MixinAfterDef(mixer, mixee))
def p_sequence_lcb_rcb(p):
'sequence : LCB RCB'
p[0] = Sequence()
p[0].lineno = get_lineno(p, 1)
def l2s(mod, temporal_goal):
# modify mod in place
# module pass helper funciton
def mod_pass(transform):
mod.labeled_conjs = [transform(x) for x in mod.labeled_conjs]
# TODO: what about axioms and properties?
for a in mod.public_actions:
action = mod.actions[a]
new_action = transform(action)
new_action.lineno = action.lineno
new_action.formal_params = action.formal_params
new_action.formal_returns = action.formal_returns
mod.actions[a] = new_action
mod.initializers = [(x, transform(y)) for x, y in mod.initializers]
l2s_waiting = lg.Const('l2s_waiting', lg.Boolean)
l2s_frozen = lg.Const('l2s_frozen', lg.Boolean)
l2s_saved = lg.Const('l2s_saved', lg.Boolean)
l2s_error = lg.Const('l2s_error', lg.Boolean)
l2s_d = lambda sort: lg.Const('l2s_d', lg.FunctionSort(sort, lg.Boolean))
l2s_a = lambda sort: lg.Const('l2s_a', lg.FunctionSort(sort, lg.Boolean))
l2s_w = lambda vs, t: lg.NamedBinder('l2s_w', vs, t)
l2s_s = lambda vs, t: lg.NamedBinder('l2s_s', vs, t)
l2s_g = lambda vs, t: lg.NamedBinder('l2s_g', vs, t)
old_l2s_g = lambda vs, t: lg.NamedBinder('old_l2s_g', vs, t)
# add conjectures about monitor state
conjs = [
lg.Or(l2s_waiting, l2s_frozen, l2s_saved),
lg.Or(lg.Not(l2s_waiting), lg.Not(l2s_frozen)),
lg.Or(lg.Not(l2s_waiting), lg.Not(l2s_saved)),
lg.Or(lg.Not(l2s_frozen), lg.Not(l2s_saved)),
]
for f in conjs:
c = ast.LabeledFormula(ast.Atom('l2s_internal'), f)
c.lineno = temporal_goal.lineno
mod.labeled_conjs.append(c)
# add conjecture that we are not in the error state (this is
# instead of using an assertion. see below)
c = ast.LabeledFormula(ast.Atom('not_l2s_error'), lg.Not(l2s_error))
c.lineno = temporal_goal.lineno
mod.labeled_conjs.append(c)
#print ilu.used_symbols_asts(mod.labeled_conjs)
#print '='*40
#print list(ilu.named_binders_asts(mod.labeled_conjs))
# some normalization
# We first convert all temporal operators to named binders, so
# it's possible to normalize them. Otherwise we won't have the
# connection betweel (globally p(X)) and (globally p(Y)). Note
# that we replace them even inside named binders.
l2s_gs = set()
def _l2s_g(vs, t):
vs = tuple(vs)
res = l2s_g(vs, t)
l2s_gs.add((vs, t))
return res
replace_temporals_by_l2s_g = lambda ast: ilu.replace_temporals_by_named_binder_g_ast(
ast, _l2s_g)
mod_pass(replace_temporals_by_l2s_g)
not_temporal_goal = replace_temporals_by_l2s_g(
lg.Not(temporal_goal.formula))
if debug.get():
print "=" * 80 + "\nafter replace_temporals_by_named_binder_g_ast" + "\n" * 3
print "=" * 80 + "\nl2s_gs:"
for vs, t in sorted(l2s_gs):
print vs, t
print "=" * 80 + "\n" * 3
print_module(mod)
print "=" * 80 + "\n" * 3
# now we normalize all named binders
mod_pass(ilu.normalize_named_binders)
if debug.get():
print "=" * 80 + "\nafter normalize_named_binders" + "\n" * 3
print_module(mod)
print "=" * 80 + "\n" * 3
# TODO: what about normalizing temporal_goal? - temporal_goal
# should not contain any named binders except for temporal
# properties, so it is normalized by construction
# construct the monitor related building blocks
uninterpreted_sorts = [
s for s in mod.sig.sorts.values() if type(s) is lg.UninterpretedSort
]
reset_a = [
AssignAction(l2s_a(s)(v),
l2s_d(s)(v)) for s in uninterpreted_sorts
for v in [lg.Var('X', s)]
]
add_consts_to_d = [
AssignAction(l2s_d(s)(c), lg.true) for s in uninterpreted_sorts
for c in mod.sig.symbols.values() if c.sort == s
]
# TODO: maybe add all ground terms, not just consts (if stratified)
# TODO: add conjectures that constants are in d and a
# figure out which l2s_w and l2s_s are used in conjectures
named_binders_conjs = defaultdict(
list) # dict mapping names to lists of (vars, body)
for b in ilu.named_binders_asts(mod.labeled_conjs):
named_binders_conjs[b.name].append((b.variables, b.body))
named_binders_conjs = defaultdict(
list, ((k, sorted(list(set(v))))
for k, v in named_binders_conjs.iteritems()))
to_wait = [
] # list of (variables, term) corresponding to l2s_w in conjectures
to_wait += named_binders_conjs['l2s_w']
to_save = [
] # list of (variables, term) corresponding to l2s_s in conjectures
to_save += named_binders_conjs['l2s_s']
if debug.get():
print "=" * 40 + "\nto_wait:\n"
for vs, t in to_wait:
print vs, t
# print list(ilu.variables_ast(t)) == list(vs)
# print
print "=" * 40
save_state = [AssignAction(l2s_s(vs, t)(*vs), t) for vs, t in to_save]
done_waiting = [forall(vs, lg.Not(l2s_w(vs, t)(*vs))) for vs, t in to_wait]
reset_w = [
AssignAction(
l2s_w(vs, t)(*vs), lg.And(*(l2s_d(v.sort)(v) for v in vs)))
for vs, t in to_wait
]
update_w = [
AssignAction(
l2s_w(vs, t)(*vs),
lg.And(
l2s_w(vs, t)(*vs), lg.Not(t),
replace_temporals_by_l2s_g(lg.Not(lg.Globally(ilu.negate(t)))))
# ($l2s_w. phi) waits until ( phi | globally ~phi), but
# ($l2s_w. ~phi) waits until (~phi | globally phi) (i.e., we avoid "globally ~~phi" here)
# note this adds to l2s_gs
) for vs, t in to_wait
]
if debug.get():
print "=" * 40 + "\nupdate_w:\n"
for x in update_w:
print x
print
print "=" * 40
fair_cycle = [l2s_saved]
fair_cycle += done_waiting
# projection of relations
fair_cycle += [
lg.ForAll(
vs,
lg.Implies(lg.And(*(l2s_a(v.sort)(v)
for v in vs)), lg.Iff(l2s_s(vs, t)(*vs), t)))
if len(vs) > 0 else lg.Iff(l2s_s(vs, t), t) for vs, t in to_save
if (t.sort == lg.Boolean or isinstance(t.sort, lg.FunctionSort)
and t.sort.range == lg.Boolean)
]
# projection of functions and constants
fair_cycle += [
forall(
vs,
lg.Implies(
lg.And(*([l2s_a(v.sort)(v) for v in vs] + [
lg.Or(l2s_a(t.sort)(l2s_s(vs, t)(*vs)),
l2s_a(t.sort)(t))
])), lg.Eq(l2s_s(vs, t)(*vs), t))) for vs, t in to_save
if (isinstance(t.sort, lg.UninterpretedSort)
or isinstance(t.sort, lg.FunctionSort)
and isinstance(t.sort.range, lg.UninterpretedSort))
]
if debug.get():
print "=" * 40 + "\nfair_cycle:\n"
for x in fair_cycle:
print x
print
print "=" * 40
# TODO: figure out why AssertAction doesn't work properly
def assert_no_fair_cycle(a):
# comment and uncomment the following lines to debug:
# res = AssertAction(lg.Not(lg.And(*fair_cycle)))
# res = AssertAction(lg.false)
# res.lineno = temporal_goal.lineno
# res.lineno = a.lineno
res = AssignAction(l2s_error, lg.And(*fair_cycle))
return res
monitor_edge = lambda s1, s2: [
AssumeAction(s1),
AssignAction(s1, lg.false),
AssignAction(s2, lg.true),
]
change_monitor_state = [
ChoiceAction(
# waiting -> frozen
Sequence(*(monitor_edge(l2s_waiting, l2s_frozen) +
[AssumeAction(x) for x in done_waiting] + reset_a)),
# frozen -> saved
Sequence(*(monitor_edge(l2s_frozen, l2s_saved) + save_state +
reset_w)),
# stay in same state (self edge)
Sequence(),
)
]
# tableau construction
to_g = [] # list of (variables, formula)
to_g += sorted(list(l2s_gs))
if debug.get():
print '=' * 40 + "\nto_g:\n"
for vs, t in to_g:
print vs, t, '\n'
print '=' * 40
assume_g_axioms = [
AssumeAction(forall(vs, lg.Implies(l2s_g(vs, t)(*vs), t)))
for vs, t in to_g
]
update_g = [
a for vs, t in to_g for a in [
HavocAction(l2s_g(vs, t)(*vs)),
AssumeAction(
forall(vs, lg.Implies(
old_l2s_g(vs, t)(*vs),
l2s_g(vs, t)(*vs)))),
AssumeAction(
forall(
vs,
lg.Implies(lg.And(lg.Not(old_l2s_g(vs, t)(
*vs)), t), lg.Not(l2s_g(vs, t)(*vs))))),
]
]
# now patch the module actions with monitor and tableau
if debug.get():
print "public_actions:", mod.public_actions
for a in mod.public_actions:
action = mod.actions[a]
add_params_to_d = [
AssignAction(l2s_d(p.sort)(p), lg.true)
for p in action.formal_params
]
new_action = concat_actions(*(
# TODO: check this with Sharon
assume_g_axioms + change_monitor_state + add_params_to_d +
update_g + [action] + assume_g_axioms + add_consts_to_d +
update_w + [assert_no_fair_cycle(action)]))
new_action.lineno = action.lineno
new_action.formal_params = action.formal_params
new_action.formal_returns = action.formal_returns
mod.actions[a] = new_action
l2s_init = [
AssignAction(l2s_waiting, lg.true),
AssignAction(l2s_frozen, lg.false),
AssignAction(l2s_saved, lg.false),
AssignAction(l2s_error, lg.false),
]
l2s_init += add_consts_to_d
l2s_init += reset_w
l2s_init += assume_g_axioms
l2s_init += [AssumeAction(not_temporal_goal)]
mod.initializers.append(('l2s_init', Sequence(*l2s_init)))
if debug.get():
print "=" * 80 + "\nafter patching actions" + "\n" * 3
print_module(mod)
print "=" * 80 + "\n" * 3
# now replace all named binders by fresh relations
named_binders = defaultdict(
list) # dict mapping names to lists of (vars, body)
for b in ilu.named_binders_asts(
chain(
mod.labeled_conjs,
mod.actions.values(),
(y for x, y in mod.initializers),
)):
named_binders[b.name].append(b)
# sort named binders according to a consistent order
named_binders = defaultdict(
list, ((k,
list(
sorted(
set(v),
key=lambda x:
(len(x.variables), str(x.variables), str(x.body)),
))) for k, v in named_binders.iteritems()))
# make sure old_l2s_g is consistent with l2s_g, so that
# old_l2s_g_X is really old l2s_g_X after the substitution
assert len(named_binders['l2s_g']) == len(named_binders['old_l2s_g'])
assert named_binders['old_l2s_g'] == [
lg.NamedBinder('old_l2s_g', b.variables, b.body)
for b in named_binders['l2s_g']
]
subs = dict((b, lg.Const('{}_{}'.format(k, i), b.sort))
for k, v in named_binders.iteritems() for i, b in enumerate(v))
if debug.get():
print "=" * 80 + "\nsubs:" + "\n" * 3
for k in sorted(named_binders.keys()):
v = named_binders[k]
for i, b in enumerate(v):
print '{}_{}'.format(k, i), ' : ', b
print "=" * 80 + "\n" * 3
mod_pass(lambda ast: ilu.replace_named_binders_ast(ast, subs))
if debug.get():
print "=" * 80 + "\nafter replace_named_binders" + "\n" * 3
print_module(mod)
print "=" * 80 + "\n" * 3
def p_action_lcb_rcb(p):
'action : LCB RCB'
p[0] = Sequence()
p[0].lineno = p.lineno(1)
def l2s(mod, lf):
# modify mod in place
# module pass helper funciton
def mod_pass(transform):
mod.labeled_conjs = [transform(x) for x in mod.labeled_conjs]
# TODO: what about axioms and properties?
for a in mod.public_actions:
action = mod.actions[a]
new_action = transform(action)
new_action.lineno = action.lineno
new_action.formal_params = action.formal_params
new_action.formal_returns = action.formal_returns
mod.actions[a] = new_action
mod.initializers = [(x, transform(y)) for x, y in mod.initializers]
l2s_waiting = lg.Const('l2s_waiting', lg.Boolean)
l2s_frozen = lg.Const('l2s_frozen', lg.Boolean)
l2s_saved = lg.Const('l2s_saved', lg.Boolean)
l2s_d = lambda sort: lg.Const('l2s_d', lg.FunctionSort(sort, lg.Boolean))
l2s_a = lambda sort: lg.Const('l2s_a', lg.FunctionSort(sort, lg.Boolean))
l2s_w = lambda vs, t: lg.NamedBinder('l2s_w', vs, t)
l2s_s = lambda vs, t: lg.NamedBinder('l2s_s', vs, t)
l2s_g = lambda vs, t: lg.NamedBinder('l2s_g', vs, t)
old_l2s_g = lambda vs, t: lg.NamedBinder('old_l2s_g', vs, t)
#print ilu.used_symbols_asts(mod.labeled_conjs)
#print '='*40
#print list(ilu.named_binders_asts(mod.labeled_conjs))
# some normalization
# We first convert all temporal operators to named binders, so
# it's possible to normalize them. Otherwise we won't have the
# connection betweel (globally p(X)) and (globally p(Y)). Note
# that we replace them even inside named binders.
l2s_gs = set()
def _l2s_g(vs, t):
vs = tuple(vs)
res = l2s_g(vs, t)
l2s_gs.add((vs, t))
return res
replace_temporals_by_l2s_g = lambda ast: ilu.replace_temporals_by_named_binder_g_ast(
ast, _l2s_g)
mod_pass(replace_temporals_by_l2s_g)
not_lf = replace_temporals_by_l2s_g(lg.Not(lf.formula))
if debug.get():
print "=" * 80 + "\nafter replace_temporals_by_named_binder_g_ast" + "\n" * 3
print "=" * 80 + "\nl2s_gs:"
for vs, t in sorted(l2s_gs):
print vs, t
print "=" * 80 + "\n" * 3
print_module(mod)
print "=" * 80 + "\n" * 3
# now we normalize all named binders
mod_pass(ilu.normalize_named_binders)
if debug.get():
print "=" * 80 + "\nafter normalize_named_binders" + "\n" * 3
print_module(mod)
print "=" * 80 + "\n" * 3
# TODO: what about normalizing lf?
# construct the monitor related building blocks
uninterpreted_sorts = [
s for s in mod.sig.sorts.values() if type(s) is lg.UninterpretedSort
]
reset_a = [
AssignAction(l2s_a(s)(v),
l2s_d(s)(v)) for s in uninterpreted_sorts
for v in [lg.Var('X', s)]
]
add_consts_to_d = [
AssignAction(l2s_d(s)(c), lg.true) for s in uninterpreted_sorts
for c in mod.sig.symbols.values() if c.sort == s
]
# TODO: maybe add all ground terms, not just consts (if stratified)
# TODO: add conjectures that constants are in d and a
# figure out which l2s_w and l2s_s are used in conjectures
named_binders_conjs = defaultdict(
list) # dict mapping names to lists of (vars, body)
for b in ilu.named_binders_asts(mod.labeled_conjs):
named_binders_conjs[b.name].append((b.variables, b.body))
named_binders_conjs = defaultdict(
list, ((k, list(set(v))) for k, v in named_binders_conjs.iteritems()))
to_wait = [
] # list of (variables, term) corresponding to l2s_w in conjectures
to_wait += named_binders_conjs['l2s_w']
to_save = [
] # list of (variables, term) corresponding to l2s_s in conjectures
to_save += named_binders_conjs['l2s_s']
if debug.get():
print "=" * 40 + "\nto_wait:\n"
for vs, t in to_wait:
print vs, t
print list(ilu.variables_ast(t)) == list(vs)
print
print "=" * 40
save_state = [AssignAction(l2s_s(vs, t)(*vs), t) for vs, t in to_save]
done_waiting = [forall(vs, lg.Not(l2s_w(vs, t)(*vs))) for vs, t in to_wait]
reset_w = [
AssignAction(
l2s_w(vs, t)(*vs), lg.And(*(l2s_d(v.sort)(v) for v in vs)))
for vs, t in to_wait
]
update_w = [
AssignAction(
l2s_w(vs, t)(*vs),
lg.And(
l2s_w(vs, t)(*vs), lg.Not(t),
replace_temporals_by_l2s_g(lg.Not(lg.Globally(lg.Not(t)))))
# TODO check this and make sure its correct
# note this adds to l2s_gs
) for vs, t in to_wait
]
if debug.get():
print "=" * 40 + "\nupdate_w:\n"
for x in update_w:
print x
print
print "=" * 40
fair_cycle = [l2s_saved]
fair_cycle += done_waiting
# projection of relations
fair_cycle += [
lg.ForAll(
vs,
lg.Implies(lg.And(*(l2s_a(v.sort)(v)
for v in vs)), lg.Iff(l2s_s(vs, t)(*vs), t)))
if len(vs) > 0 else lg.Iff(l2s_s(vs, t), t) for vs, t in to_save
if (t.sort == lg.Boolean or isinstance(t.sort, lg.FunctionSort)
and t.sort.range == lg.Boolean)
]
# projection of functions and constants
fair_cycle += [
forall(
vs,
lg.Implies(
lg.And(*([l2s_a(v.sort)(v) for v in vs] + [
lg.Or(l2s_a(t.sort)(l2s_s(vs, t)(*vs)),
l2s_a(t.sort)(t))
])), lg.Eq(l2s_s(vs, t)(*vs), t))) for vs, t in to_save
if (isinstance(t.sort, lg.UninterpretedSort)
or isinstance(t.sort, lg.FunctionSort)
and isinstance(t.sort.range, lg.UninterpretedSort))
]
assert_no_fair_cycle = AssertAction(lg.Not(lg.And(*fair_cycle)))
assert_no_fair_cycle.lineno = lf.lineno
monitor_edge = lambda s1, s2: [
AssumeAction(s1),
AssignAction(s1, lg.false),
AssignAction(s2, lg.true),
]
change_monitor_state = [
ChoiceAction(
# waiting -> frozen
Sequence(*(monitor_edge(l2s_waiting, l2s_frozen) +
[AssumeAction(x) for x in done_waiting] + reset_a)),
# # frozen -> saved
# Sequence(*(
# monitor_edge(l2s_frozen, l2s_saved) +
# save_state +
# reset_w
# )),
# stay in same state (self edge)
Sequence(),
)
]
# tableau construction (sort of)
# Note that we first transformed globally and eventually to named
# binders, in order to normalize. Without this, we would get
# multiple redundant axioms like:
# forall X. (globally phi(X)) -> phi(X)
# forall Y. (globally phi(Y)) -> phi(Y)
# and the same redundancy will happen for transition updates.
# temporals = []
# temporals += list(ilu.temporals_asts(
# # TODO: these should be handled by mod_pass instead (and come via l2s_gs):
# # mod.labeled_axioms +
# # mod.labeled_props +
# [lf]
# ))
# temporals += [lg.Globally(lg.Not(t)) for vs, t in to_wait]
# temporals += [lg.Globally(t) for vs, t in l2s_gs]
# # TODO get from temporal axioms and temporal properties as well
# print '='*40 + "\ntemporals:"
# for t in temporals:
# print t, '\n'
# print '='*40
# to_g = [ # list of (variables, formula)
# (tuple(sorted(ilu.variables_ast(tt))), tt) # TODO what about variable normalization??
# for t in temporals
# for tt in [t.body if type(t) is lg.Globally else
# lg.Not(t.body) if type(t) is lg.Eventually else 1/0]
# ]
# TODO: get rid of the above, after properly combining it
to_g = [] # list of (variables, formula)
to_g += list(l2s_gs)
to_g = list(set(to_g))
if debug.get():
print '=' * 40 + "\nto_g:\n"
for vs, t in sorted(to_g):
print vs, t, '\n'
print '=' * 40
assume_g_axioms = [
AssumeAction(forall(vs, lg.Implies(l2s_g(vs, t)(*vs), t)))
for vs, t in to_g
]
update_g = [
a for vs, t in to_g for a in [
HavocAction(l2s_g(vs, t)(*vs)),
AssumeAction(
forall(vs, lg.Implies(
old_l2s_g(vs, t)(*vs),
l2s_g(vs, t)(*vs)))),
AssumeAction(
forall(
vs,
lg.Implies(lg.And(lg.Not(old_l2s_g(vs, t)(
*vs)), t), lg.Not(l2s_g(vs, t)(*vs))))),
]
]
# now patch the module actions with monitor and tableau
if debug.get():
print "public_actions:", mod.public_actions
# TODO: this includes the succ action (for the ticket example of
# test/test_liveness.ivy). seems to be a bug, and this causes
# wrong behavior for the monitor, since a call to succ from within
# another action lets it take a step
for a in mod.public_actions:
action = mod.actions[a]
add_params_to_d = [
AssignAction(l2s_d(p.sort)(p), lg.true)
for p in action.formal_params
]
new_action = concat_actions(*(change_monitor_state + add_params_to_d +
update_g + [action] + assume_g_axioms +
add_consts_to_d + update_w +
[assert_no_fair_cycle]))
new_action.lineno = action.lineno
new_action.formal_params = action.formal_params
new_action.formal_returns = action.formal_returns
mod.actions[a] = new_action
l2s_init = [
AssignAction(l2s_waiting, lg.true),
AssignAction(l2s_frozen, lg.false),
AssignAction(l2s_saved, lg.false),
]
l2s_init += add_consts_to_d
l2s_init += reset_w
l2s_init += assume_g_axioms
l2s_init += [AssumeAction(not_lf)]
mod.initializers.append(('l2s_init', Sequence(*l2s_init)))
if debug.get():
print "=" * 80 + "\nafter patching actions" + "\n" * 3
print_module(mod)
print "=" * 80 + "\n" * 3
# now replace all named binders by fresh relations
named_binders = defaultdict(
list) # dict mapping names to lists of (vars, body)
for b in ilu.named_binders_asts(
chain(
mod.labeled_conjs,
mod.actions.values(),
(y for x, y in mod.initializers),
)):
named_binders[b.name].append(b)
named_binders = defaultdict(list, ((k, list(sorted(set(v))))
for k, v in named_binders.iteritems()))
# make sure old_l2s_g is consistent with l2s_g
assert len(named_binders['l2s_g']) == len(named_binders['old_l2s_g'])
assert named_binders['old_l2s_g'] == [
lg.NamedBinder('old_l2s_g', b.variables, b.body)
for b in named_binders['l2s_g']
]
subs = dict((b, lg.Const('{}_{}'.format(k, i), b.sort))
for k, v in named_binders.iteritems() for i, b in enumerate(v))
if debug.get():
print "=" * 80 + "\nsubs:" + "\n" * 3
for k, v in subs.items():
print k, ' : ', v, '\n'
print "=" * 80 + "\n" * 3
mod_pass(lambda ast: ilu.replace_named_binders_ast(ast, subs))
if debug.get():
print "=" * 80 + "\nafter replace_named_binders" + "\n" * 3
print_module(mod)
print "=" * 80 + "\n" * 3
def p_sequence_lcb_actseq_semi_rcb(p):
'sequence : LCB actseq SEMI RCB'
p[0] = Sequence(*lower_var_stmts(p[2]))
p[0].lineno = get_lineno(p, 1)
