def test_benchmark_summary():
experiment_df = create_experiment_data()
benchmark_df = experiment_df[experiment_df.benchmark == 'libxml']
snapshot_df = data_utils.get_benchmark_snapshot(benchmark_df)
summary = data_utils.benchmark_summary(snapshot_df)
expected_summary = pd.DataFrame({
'fuzzer': ['afl', 'libfuzzer'],
'time': [9, 9],
'count': [2, 2],
'min': [1000, 600],
'median': [1100, 700],
'max': [1200, 800]
}).set_index(['fuzzer', 'time']).astype(float)
assert summary[['count', 'min', 'median', 'max']].equals(expected_summary)
def summary_table(self):
"""Statistical summary table."""
return data_utils.benchmark_summary(self._benchmark_snapshot_df)
def bug_summary_table(self):
"""Statistical summary table."""
return data_utils.benchmark_summary(self._benchmark_snapshot_df,
key='bugs_covered')