def main():
env = gym.make('FuzzLibPNG-v0')
print("dict_size={} eof={}".format(env.dict_size(), env.eof()))
env.reset()
c = coverage.Coverage()
inputs = [
[1, env.eof()] + [0] * 1022,
[env.eof()] + [0] * 1023,
[1, env.eof()] + [0] * 1022,
]
for i in inputs:
obs, reward, done, info = env.step(np.array(i))
c.add(info['step_coverage'])
print(("STEP: reward={} done={} " +
"step={}/{}/{} total={}/{}/{} " +
"sum={}/{}/{} action={}").format(
reward, done,
info['step_coverage'].skip_path_count(),
info['step_coverage'].transition_count(),
info['step_coverage'].crash_count(),
info['total_coverage'].skip_path_count(),
info['total_coverage'].transition_count(),
info['total_coverage'].crash_count(),
c.skip_path_count(),
c.transition_count(),
c.crash_count(),
i[:13],
))
if done:
env.reset()
print("DONE!")
def main():
env = gym.make('FuzzSimpleBits-v0')
print("dict_size={} eof={}".format(env.dict_size(), env.eof()))
env.reset()
c = coverage.Coverage()
inputs = [
[1, 256] + [0] * 62,
[256] + [0] * 63,
[1, 1, 256] + [0] * 61,
[1, 1, 256] + [0] * 61,
[1, 1, 256] + [0] * 61,
[12, 256] + [0] * 62,
[12, 7, 256] + [0] * 61,
[1, 256] + [0] * 62,
[1, 2, 256] + [0] * 61,
[1, 2, 3, 256] + [0] * 60,
[1, 2, 3, 4, 256] + [0] * 59,
[1, 2, 3, 4, 5, 256] + [0] * 58,
[1, 1, 256] + [0] * 61,
[1, 1, 256] + [0] * 61,
[0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 256] + [0] * 53,
[0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 256] + [0] * 52,
[0, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1, 0, 256] + [0] * 51,
[1, 1, 256] + [0] * 61,
]
for i in inputs:
obs, reward, done, info = env.step(np.array(i))
c.add(info['step_coverage'])
print('obs coords where > 0: ', np.where(np.array(obs) > 0))
print('input_data used:', info['input_data'])
print(("STEP: reward={} done={} " + "step={}/{}/{} total={}/{}/{} " +
"sum={}/{}/{} action={}").format(
reward,
done,
info['step_coverage'].skip_path_count(),
info['step_coverage'].transition_count(),
info['step_coverage'].crash_count(),
info['total_coverage'].skip_path_count(),
info['total_coverage'].transition_count(),
info['total_coverage'].crash_count(),
c.skip_path_count(),
c.transition_count(),
c.crash_count(),
i[:13],
))
if done:
env.reset()
print("DONE!")
def main():
env = gym.make('FuzzSimpleBits-v0')
print("dict_size={} eof={}".format(env.dict_size(), env.eof()))
MAX_STEPS = 5000
env.reset()
c = coverage.Coverage()
for _ in range(MAX_STEPS):
# take a random action. If there's an RL agent, the agent would control
# action selection.
obs, reward, done, info = env.step(env.action_space.sample())
# print('obs coords where > 0: ', np.where(np.array(obs) > 0)) # debug
print('input_data used:', info['input_data'])
if info['action'] == 'run':
c.add(info['step_coverage']) # update records
print(
("STEP: reward={} done={} " + "step={}/{}/{} total={}/{}/{} " +
"sum={}/{}/{} action={}").format(
reward,
done,
info['step_coverage'].skip_path_count(),
info['step_coverage'].transition_count(),
info['step_coverage'].crash_count(),
info['total_coverage'].skip_path_count(),
info['total_coverage'].transition_count(),
info['total_coverage'].crash_count(),
c.skip_path_count(),
c.transition_count(),
c.crash_count(),
info['action'],
))
else:
print(("STEP: reward={} done={} action={}").format(
reward, done, info['action']))
if done:
env.reset()
print("ENV RESET")
def reset(self):
self.total_coverage = coverage.Coverage()
return coverage.Coverage().observation()