def explore(self, current_patch, current_fitness):
assert self.debug_patch is not None
self.report['best_fitness'] = None
self.report['best_patch'] = None
for edit in cleaned_patch.edit_list:
# move
patch = Patch(self.program)
patch.add(edit)
# compare
run = self.evaluate_patch(patch)
h = [self.stats['steps'] + 1, run.status, ' ', run.fitness, patch]
if run.status == 'SUCCESS':
accept = True
if self.dominates(run.fitness, self.report['best_fitness']):
self.report['best_fitness'] = run.fitness
self.report['best_patch'] = patch
h[2] = '*'
# log
self.program.logger.debug(self.program.diff(patch))
self.program.logger.debug(run)
self.program.logger.info('{}\t{}\t{}{}\t{}'.format(*h))
# next
self.stats['steps'] += 1
self.report['stop'] = 'validation end'
return current_patch, current_fitness
def test_diff(self, setup_tree):
program = setup_tree
patch = Patch(program)
assert not program.diff(patch).strip()
patch.add(
StmtInsertion(('triangle.py', 1), ('triangle.py', 10),
direction='after'))
assert program.diff(patch).strip()
def test_diff(self, setup_tree):
program = setup_tree
patch = Patch()
print(patch.raw())
assert not program.diff(patch).strip()
patch.add(
StmtInsertion(('triangle.py', 'stmt', 1),
('triangle.py', 'stmt', 10)))
assert program.diff(patch).strip()
def crossover(self, sol1, sol2):
c = Patch(self.program)
k1 = random.randint(0, len(sol1))
k2 = random.randint(0, len(sol2))
for edit in sol1.edit_list[:k1]:
c.add(edit)
for edit in sol2.edit_list[k2:]:
c.add(edit)
return c
def explore(self, current_patch, current_fitness):
if self.debug_patch is None:
raise ValueError()
self.cleaned_patch = self.do_clean_patch(self.debug_patch)
self.program.logger.debug('CLEAN_PATCH: {}'.format(str(self.cleaned_patch)))
self.program.logger.debug('CLEAN_SIZE: %d (was %d)', len(self.cleaned_patch), len(self.debug_patch))
self.report['best_fitness'] = None
self.report['best_patch'] = None
self.report['cleaned_patch'] = self.cleaned_patch
# full patch first
if self.debug_patch.edit_list:
run = self.do_eval_patch(self.debug_patch)
else:
self.report['stop'] = 'validation end (empty patch)'
return current_patch, current_fitness
# ranking
self.program.logger.info('-- ranking --')
ranking = list()
for edit in self.debug_patch.edit_list:
patch = Patch([edit])
run = self.do_eval_patch(patch)
if run.fitness:
ranking.append((edit, run.fitness))
ranking.sort(key=lambda c: c[1])
# rebuild
if ranking[0][1] > self.report['initial_fitness']:
self.program.logger.info('-- rebuild --')
rebuild = Patch(ranking[0])
rebuild_fitness = ranking[0][1]
for (edit,fit) in ranking[1:]:
patch = copy.deepcopy(rebuild)
patch.add(edit)
run = self.do_eval_patch(patch)
if run.status == 'SUCCESS' and self.dominates(run.fitness, rebuild_fitness):
rebuild_fitness = run.fitness
rebuild.add(edit)
# round robin ablation
self.program.logger.info('-- ablation --')
n = len(self.debug_patch.edit_list)+1
last_i = 0
while n > len(self.report['best_patch'].edit_list):
n = len(self.report['best_patch'].edit_list)
for i in range(n):
patch = Patch([e for (j, e) in enumerate(self.report['best_patch'].edit_list) if (j+last_i)%n != i])
run = self.do_eval_patch(patch)
if run.fitness == self.report['best_fitness']:
self.report['best_patch'] = patch # accept because smaller
last_i = i # round robin
break
self.report['stop'] = 'validation end'
return current_patch, current_fitness
def test_apply(self, setup_tree):
program = setup_tree
patch = Patch()
patch.add(
StmtInsertion(('triangle.py', 'stmt', 1),
('triangle.py', 'stmt', 10)))
program.apply(patch)
file_contents = open(os.path.join(program.work_path, 'triangle.py'),
'r').read()
assert file_contents == program.dump(
program.get_modified_contents(patch), 'triangle.py')
def test_apply(self, setup_line):
program = setup_line
patch = Patch(program)
patch.add(
LineInsertion(('triangle.py', 1), ('triangle.py', 10),
direction='after'))
program.apply(patch)
file_contents = open(os.path.join(program.tmp_path, 'triangle.py'),
'r').read()
assert file_contents == program.dump(
program.get_modified_contents(patch), 'triangle.py')
def crossover(self, sol1, sol2):
c = Patch(self.program)
for edit in sol1.edit_list:
if random.random() > self.config['uniform_rate']:
c.add(edit)
for edit in sol2.edit_list:
if random.random() > self.config['uniform_rate']:
c.add(edit)
if len(c) == 0:
sol3, sol4 = [sol1, sol2
] if random.random() > 0.5 else [sol2, sol1]
if len(sol3) > 0:
c.add(random.choice(sol3.edit_list))
elif len(sol4) > 0:
c.add(random.choice(sol4.edit_list))
return c
def crossover(self, sol1, sol2):
c = Patch(self.program)
k1 = random.randint(0, len(sol1))
k2 = random.randint(0, len(sol1))
k3 = random.randint(0, len(sol2))
k4 = random.randint(0, len(sol2))
for edit in sol1.edit_list[:min(k1, k2)]:
c.add(edit)
for edit in sol2.edit_list[min(k3, k4):max(k3, k4)]:
c.add(edit)
for edit in sol1.edit_list[max(k1, k2):]:
c.add(edit)
return c
def explore(self, current_patch, current_fitness):
if self.debug_patch is None:
raise ValueError()
self.cleaned_patch = self.do_clean_patch(self.debug_patch)
self.program.logger.debug('CLEAN_PATCH: {}'.format(str(self.cleaned_patch)))
self.program.logger.debug('CLEAN_SIZE: %d (was %d)', len(self.cleaned_patch), len(self.debug_patch))
self.report['best_fitness'] = None
self.report['best_patch'] = None
self.report['cleaned_patch'] = self.cleaned_patch
# full patch first
if self.debug_patch.edit_list:
self.do_eval_patch(self.debug_patch)
else:
self.report['stop'] = 'validation end (empty patch)'
return current_patch, current_fitness
# ranking
ranking = list()
for edit in self.debug_patch.edit_list:
patch = Patch([edit])
run = self.do_eval_patch(patch)
ranking.append((edit, run.fitness))
ranking.sort(key=lambda c: c[1])
if ranking[0][1] > self.report['initial_fitness']:
self.report['stop'] = 'validation end (all bad)'
return current_patch, current_fitness
# rebuild
rebuild = Patch()
rebuild_fitness = None
for (k,(edit,fit)) in enumerate(ranking):
# move
patch = copy.deepcopy(rebuild)
patch.add(edit)
# compare
if k == 0:
rebuild.add(edit)
rebuild_fitness = fit
continue
run = self.do_eval_patch(patch)
if run.status == 'SUCCESS' and self.dominates(run.fitness, rebuild_fitness):
rebuild_fitness = run.fitness
rebuild.add(edit)
self.report['stop'] = 'validation end'
return current_patch, current_fitness
def crossover(self, sol1, sol2):
c = Patch(self.program)
l1 = [(i / len(sol1), 0) for i in sorted(
random.sample(range(len(sol1)),
math.ceil(len(sol1) * self.config['uniform_rate'])))]
l2 = [(i / len(sol2), 1) for i in sorted(
random.sample(range(len(sol2)),
math.ceil(len(sol2) * self.config['uniform_rate'])))]
for (x, k) in sorted(l1 + l2):
sol = [sol1, sol2][k]
edit = sol.edit_list[int(x * len(sol))]
c.add(edit)
if len(c) == 0:
sol3, sol4 = [sol1, sol2
] if random.random() > 0.5 else [sol2, sol1]
if len(sol3) > 0:
c.add(random.choice(sol3.edit_list))
elif len(sol4) > 0:
c.add(random.choice(sol4.edit_list))
return c
def explore(self, current_patch, current_fitness):
assert self.debug_patch is not None
self.cleaned_patch = self.clean_patch(self.debug_patch)
self.program.logger.debug('CLEAN_PATCH: {}'.format(
str(self.cleaned_patch)))
self.program.logger.debug('CLEAN_SIZE: %d (was %d)',
len(self.cleaned_patch),
len(self.debug_patch))
self.report['best_fitness'] = None
self.report['best_patch'] = None
# ranking
ranking = list()
for edit in cleaned_patch.edit_list:
# move
patch = Patch(self.program)
patch.add(edit)
# compare
run = self.evaluate_patch(patch)
accept = best = False
if run.status == 'SUCCESS':
accept = True
if self.dominates(run.fitness, self.report['best_fitness']):
self.report['best_fitness'] = run.fitness
self.report['best_patch'] = patch
best = True
ranking.append((edit, run.fitness))
# hook
self.hook_evaluation(patch, run, accept, best)
# next
self.stats['steps'] += 1
# rebuild
ranking.sort(key=lambda c: c[1])
rebuild = Patch(self.program)
# todo: fail if first bad
for (k, (edit, _)) in enumerate(ranking):
# move
patch = copy.deepcopy(rebuild)
patch.add(edit)
# compare
if k == 0:
rebuild.add(edit)
continue
run = self.evaluate_patch(patch)
accept = best = False
if run.status == 'SUCCESS':
accept = True
# todo: accept only over a threshold
if self.dominates(run.fitness, self.report['best_fitness']):
self.program.logger.debug(self.program.diff(patch))
self.report['best_fitness'] = run.fitness
self.report['best_patch'] = patch
best = True
rebuild.add(edit)
# hook
self.hook_evaluation(patch, run, accept, best)
# next
self.stats['steps'] += 1
self.report['stop'] = 'validation end'
return current_patch, current_fitness
def eval_patch(program, string):
patch = Patch(program)
for s in string.split(' | '):
patch.add(eval_edit(s))
return patch