def test_interesting_linear_series_exprs():
pairs = set([pair for f in pairings for pair in pairings[f]])
notes = {}
for pair in pairs:
p = check.build_problem(pair)
for n in search.init_loops_to_split(p, ()):
intr = logic.interesting_linear_series_exprs(p, n, search.get_loop_var_analysis_at(p, n))
if intr:
notes[pair.name] = True
if "Call" in str(intr):
notes[pair.name] = "Call!"
return notes
def test_interesting_linear_series_exprs():
pairs = set([pair for f in pairings for pair in pairings[f]])
notes = {}
for pair in pairs:
p = check.build_problem(pair)
for n in search.init_loops_to_split(p, ()):
intr = logic.interesting_linear_series_exprs(
p, n, search.get_loop_var_analysis_at(p, n))
if intr:
notes[pair.name] = True
if 'Call' in str(intr):
notes[pair.name] = 'Call!'
return notes
def candidate_additional_eqs(p, split):
eq_vals = set()
def visitor(expr):
if expr.is_op('Equals') and expr.vals[0].typ.kind == 'Word':
[x, y] = expr.vals
eq_vals.update([(x, y), (y, x)])
for n in p.loop_body(split):
p.nodes[n].visit(lambda x: (), visitor)
for (x, y) in list(eq_vals):
if is_zero(x) and y.is_op('Plus'):
[x, y] = y.vals
eq_vals.add((x, syntax.mk_uminus(y)))
eq_vals.add((y, syntax.mk_uminus(x)))
elif is_zero(x) and y.is_op('Minus'):
[x, y] = y.vals
eq_vals.add((x, y))
eq_vals.add((y, x))
loop = syntax.mk_var('%i', syntax.word32T)
minus_loop_step = syntax.mk_uminus(loop)
vas = search.get_loop_var_analysis_at(p, split)
ls_vas = dict([(var, [data]) for (var, data) in vas
if data[0] == 'LoopLinearSeries'])
cmp_series = [(x, y, rew, offs) for (x, y) in eq_vals
for (_, rew, offs) in ls_vas.get(x, [])]
odd_eqs = []
for (x, y, rew, offs) in cmp_series:
x_init_cmp1 = syntax.mk_less_eq(x, rew(x, minus_loop_step))
x_init_cmp2 = syntax.mk_less_eq(rew(x, minus_loop_step), x)
fin_cmp1 = syntax.mk_less(x, y)
fin_cmp2 = syntax.mk_less(y, x)
odd_eqs.append(syntax.mk_eq(x_init_cmp1, fin_cmp1))
odd_eqs.append(syntax.mk_eq(x_init_cmp2, fin_cmp1))
odd_eqs.append(syntax.mk_eq(x_init_cmp1, fin_cmp2))
odd_eqs.append(syntax.mk_eq(x_init_cmp2, fin_cmp2))
ass_eqs = []
var_deps = p.compute_var_dependencies()
for hook in target_objects.hooks('extra_wcet_assertions'):
for assn in hook(var_deps[split]):
ass_eqs.append(assn)
return odd_eqs + ass_eqs
def var_analysis(p, n):
va = search.get_loop_var_analysis_at(p, n)
cats = {}
for (v, kind) in va:
if kind[0] == 'LoopLinearSeries':
offs = kind[2]
kind = kind[0]
else:
offs = None
cats.setdefault(kind, [])
cats[kind].append((v, offs))
for kind in cats:
print '%s:' % kind
for (v, offs) in cats[kind]:
print ' %s (%s)' % (syntax.pretty_expr(v),
syntax.pretty_type(v.typ))
if offs:
print ' ++ %s' % syntax.pretty_expr(offs)
def candidate_additional_eqs(p, split):
eq_vals = set()
def visitor(expr):
if expr.is_op("Equals") and expr.vals[0].typ.kind == "Word":
[x, y] = expr.vals
eq_vals.update([(x, y), (y, x)])
for n in p.loop_body(split):
p.nodes[n].visit(lambda x: (), visitor)
for (x, y) in list(eq_vals):
if is_zero(x) and y.is_op("Plus"):
[x, y] = y.vals
eq_vals.add((x, syntax.mk_uminus(y)))
eq_vals.add((y, syntax.mk_uminus(x)))
elif is_zero(x) and y.is_op("Minus"):
[x, y] = y.vals
eq_vals.add((x, y))
eq_vals.add((y, x))
loop = syntax.mk_var("%i", syntax.word32T)
minus_loop_step = syntax.mk_uminus(loop)
vas = search.get_loop_var_analysis_at(p, split)
ls_vas = dict([(var, [data]) for (var, data) in vas if data[0] == "LoopLinearSeries"])
cmp_series = [(x, y, rew, offs) for (x, y) in eq_vals for (_, rew, offs) in ls_vas.get(x, [])]
odd_eqs = []
for (x, y, rew, offs) in cmp_series:
x_init_cmp1 = syntax.mk_less_eq(x, rew(x, minus_loop_step))
x_init_cmp2 = syntax.mk_less_eq(rew(x, minus_loop_step), x)
fin_cmp1 = syntax.mk_less(x, y)
fin_cmp2 = syntax.mk_less(y, x)
odd_eqs.append(syntax.mk_eq(x_init_cmp1, fin_cmp1))
odd_eqs.append(syntax.mk_eq(x_init_cmp2, fin_cmp1))
odd_eqs.append(syntax.mk_eq(x_init_cmp1, fin_cmp2))
odd_eqs.append(syntax.mk_eq(x_init_cmp2, fin_cmp2))
ass_eqs = []
var_deps = p.compute_var_dependencies()
for hook in target_objects.hooks("extra_wcet_assertions"):
for assn in hook(var_deps[split]):
ass_eqs.append(assn)
return odd_eqs + ass_eqs
def problem_var_analysis_nonempty ((p, pn, restrs, hyps)): loop_head = pn.split[0][0] va = search.get_loop_var_analysis_at (p, loop_head) return bool ([v for (v, data) in va if data == 'LoopVariable'])
def loop_num_leaves(p, n):
for n in p.loop_body(n):
va = search.get_loop_var_analysis_at(p, n)
n_leaf = len([1 for (v, kind) in va if kind == 'LoopLeaf'])
print(n, n_leaf)
