def mk_seq_eqs (p, split, step, with_rodata):
# eqs take the form of a number of constant expressions
eqs = []
# the variable 'loop' will be converted to the point in
# the sequence - note this should be multiplied by the step size
loop = mk_var ('%i', word32T)
if step == 1:
minus_loop_step = mk_uminus (loop)
else:
minus_loop_step = mk_times (loop, mk_word32 (- step))
for (var, data) in get_loop_var_analysis_at (p, split):
if data == 'LoopVariable':
if with_rodata and var.typ == builtinTs['Mem']:
eqs.append (logic.mk_rodata (var))
elif data == 'LoopConst':
if var.typ not in syntax.phantom_types:
eqs.append (var)
elif data == 'LoopLeaf':
continue
elif data[0] == 'LoopLinearSeries':
(_, form, _) = data
eqs.append (form (var, minus_loop_step))
else:
assert not 'var_deps type understood'
return eqs
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 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
