diff options
| -rw-r--r-- | tools/auto_bisect/bisect_results.py | 18 |
1 files changed, 8 insertions, 10 deletions
diff --git a/tools/auto_bisect/bisect_results.py b/tools/auto_bisect/bisect_results.py index 926479d..f6ba0d8 100644 --- a/tools/auto_bisect/bisect_results.py +++ b/tools/auto_bisect/bisect_results.py @@ -105,9 +105,9 @@ class BisectResults(object): 'Failed to re-test reverted culprit CL against ToT.') return - confidence_params = (results_reverted[0]['values'], - results_tot[0]['values']) - confidence = BisectResults.ConfidenceScore(*confidence_params) + confidence = BisectResults.ConfidenceScore( + results_reverted[0]['values'], + results_tot[0]['values']) self.retest_results_tot = RevisionState('ToT', 'n/a', 0) self.retest_results_tot.value = results_tot[0] @@ -247,14 +247,12 @@ class BisectResults(object): [working_mean, broken_mean]) / max(0.0001, min(mean_of_good_runs, mean_of_bad_runs))) * 100.0 - # Give a "confidence" in the bisect. Currently, we consider the values of - # only the revisions at the breaking range (last known good and first known - # bad) see the note in the docstring for FindBreakingRange. - confidence_params = ( + # Give a "confidence" in the bisect culprit by seeing whether the results + # of the culprit revision and the revision before that appear to be + # statistically significantly different. + confidence = cls.ConfidenceScore( sum([first_working_rev.value['values']], []), - sum([last_broken_rev.value['values']], []) - ) - confidence = cls.ConfidenceScore(*confidence_params) + sum([last_broken_rev.value['values']], [])) bad_greater_than_good = mean_of_bad_runs > mean_of_good_runs |