def context_complexity(context):
result = 0
for arg in iter_shared_list(context.stack):
result += complexity(arg)
for var in iter_shared_list(context.bound):
result += complexity(var)
return result
def _collect(continuations, nonlinear):
PROFILE_COUNTERS[_collect, '...'] += 1
# Collect unique samples.
samples = set()
for continuation in continuations:
sample = _close(continuation, nonlinear)
if sample is TOP:
return TOP
samples.add(sample)
if not samples:
return BOT
# Filter out dominated samples.
# FIXME If x [= y and y [= x, this filters out both.
filtered_samples = []
for sample in samples:
if not any(oracle.try_decide_less(sample, other)
for other in samples
if other is not sample):
filtered_samples.append(sample)
filtered_samples.sort(key=lambda code: (complexity(code), code))
# Construct a join term.
result = filtered_samples[0]
for sample in filtered_samples[1:]:
result = JOIN(result, sample)
return result
def priority(code):
return is_normal(code), complexity(code), code
def test_complexity(code, expected):
assert complexity(code) == expected
def test_complexity_runs(code):
complexity(code)
def continuation_complexity(continuation):
head, context = continuation
return complexity(head) + context_complexity(context)