def main(encrypt=True):
# Inject the delta data for every binary
print('************ Injecting delta data **********')
with concurrent.futures.ProcessPoolExecutor() as executor:
for seed_tuple in support.all_seeds_gen():
for subset in support.subsets_gen(seed_tuple, False):
for (benchmark, name) in support.benchmarks_gen():
executor.submit(inject_data, benchmark, name, subset,
encrypt)
def main():
# Start with destroying the previous directory structure, if it exists
shutil.rmtree(config.data_dir, True)
# Get the seeds and extract the data for the associated build
with concurrent.futures.ProcessPoolExecutor() as executor:
for seed_tuple in support.all_seeds_gen():
for subset in support.subsets_gen(seed_tuple, False):
executor.submit(extract_data, subset)
executor.submit(extract_data, ())
def main():
# Start with destroying the previous directory structure, if it exists
shutil.rmtree(config.patches_dir, True)
# Create the patches by submitting tasks to the executor
print('************ Creating patches **********')
with concurrent.futures.ProcessPoolExecutor() as executor:
for seed_tuple in support.all_seeds_gen():
for subset in support.subsets_gen(seed_tuple, False):
for (benchmark, _) in support.benchmarks_gen():
executor.submit(create_patch, benchmark, subset)
def main():
# Create the sheet
print('************ Creating report on binary sizes **********')
sheet = pyexcel.Sheet()
rownames = [benchmark for benchmark, _ in support.benchmarks_gen()]
sheet.column += ['Binary default'] + rownames + ['Binary diversified'
] + rownames
# Get all the sizes of the default binaries
sizes = ['']
for (benchmark, name) in support.benchmarks_gen():
binary = os.path.join(support.create_path_for_seeds(config.build_dir),
benchmark, name)
if os.path.exists(binary):
sizes.append(get_binary_stripped_size(binary))
else:
sizes.append('FAIL')
# Create the AVG and MAX columns
sheet.column += sizes + ['AVG'] + [''] * len(rownames)
sheet.column += sizes + ['MAX'] + [''] * len(rownames)
for seeds in support.all_seeds_gen():
# Get all the sizes of the diversified binaries
sizes = [''] * (len(rownames) + 2)
for (benchmark, name) in support.benchmarks_gen():
binary = os.path.join(
support.create_path_for_seeds(config.build_dir, *seeds),
benchmark, name)
if os.path.exists(binary):
sizes.append(get_binary_stripped_size(binary))
else:
sizes.append('FAIL')
sheet.column += sizes
# Calculate in the average and the max
for row in (row for row in sheet.rows()
if not row[0].startswith('Binary')):
sizes = [elem for elem in row[3:] if isinstance(elem, int)]
if sizes:
row[1] = sum(sizes) // len(sizes)
row[2] = max(sizes)
# Create the report book and write it out
report = pyexcel.Book(sheets={'Sizes': sheet})
report.save_as(os.path.join(config.reports_dir, 'binary_sizes.ods'))
def main():
# Create the sheet
print('************ Creating report on patch timing **********')
sheet = pyexcel.Sheet()
rownames = [benchmark for benchmark, _ in support.benchmarks_gen()]
sheet.column += ['Patch creation'] + rownames + ['Patch application'
] + rownames
sheet.column += [''] * (len(rownames) + 1) + ['AVG'] + [''] * len(rownames)
sheet.column += [''] * (len(rownames) + 1) + ['MAX'] + [''] * len(rownames)
for seeds in support.all_seeds_gen():
# Empty cell
times = ['']
for (benchmark, name) in support.benchmarks_gen():
# Determine all paths
base_data = os.path.join(
support.create_path_for_seeds(config.data_dir), benchmark)
div_symfile_path = os.path.join(
support.create_path_for_seeds(config.data_dir, *seeds),
benchmark, 'symfile')
# Time patch creation
def time_function1():
patch.patch(base_data,
seeds,
div_symfile_path=div_symfile_path,
output_dir=config.tmp_dir)
times.append(timeit.timeit(time_function1, number=1))
shutil.copyfile(os.path.join(config.tmp_dir, 'patch'),
os.path.join(config.tmp_dir, 'patch.' + name))
# Empty cell
times.append('')
for (benchmark, name) in support.benchmarks_gen():
base_data = os.path.join(
support.create_path_for_seeds(config.data_dir), benchmark)
# Time patch application
def time_function2():
patch.patch(base_data,
seeds,
patch_path=os.path.join(config.tmp_dir,
'patch.' + name),
output_dir=config.tmp_dir)
times.append(timeit.timeit(time_function2, number=1))
sheet.column += times
# Calculate in the average and the max
for row in (row for row in sheet.rows() if not row[0].startswith('Patch')):
times = [elem for elem in row[3:] if isinstance(elem, float)]
if times:
row[1] = float(sum(times) / len(times))
row[2] = max(times)
# Create the report book and write it out
report = pyexcel.Book(sheets={'Timing': sheet})
report.save_as(os.path.join(config.reports_dir, 'patch_timing.ods'))