I noticed that when plotting the 'Mean code coverage growth over time' graph, np.median is used as the estimator (L166):
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axes = sns.lineplot( |
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y=column_of_interest, |
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x='time', |
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hue='fuzzer', |
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hue_order=fuzzer_order, |
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data=benchmark_df[benchmark_df.time <= snapshot_time], |
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ci=None if bugs or self._quick else 95, |
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estimator=np.median, |
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palette=self._fuzzer_colors, |
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style='fuzzer', |
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dashes=False, |
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markers=self._fuzzer_markers, |
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ax=axes) |
Shouldn't np.mean be used instead? For example, the order of this graph uses benchmark_rank_by_mean:
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fuzzer_order = data_utils.benchmark_rank_by_mean( |
Is there a specific reason for using np.median here, or am I missing something?
Looking forward to your insights. Thanks.
I noticed that when plotting the 'Mean code coverage growth over time' graph,
np.medianis used as the estimator (L166):fuzzbench/analysis/plotting.py
Lines 159 to 171 in 2920e74
Shouldn't
np.meanbe used instead? For example, the order of this graph usesbenchmark_rank_by_mean:fuzzbench/analysis/plotting.py
Line 156 in 2920e74
Is there a specific reason for using np.median here, or am I missing something?
Looking forward to your insights. Thanks.