History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"regressions"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
847 | 2025-09-13 02:52:05 | regressions | 1 | 49908 | 4 | 0.860 | 58032.6 |
846 | 2025-09-12 11:43:38 | regressions | 1 | 49908 | 4 | 0.906 | 55086.1 |
845 | 2025-09-10 19:49:12 | regressions | 1 | 49908 | 4 | 0.920 | 54247.8 |
844 | 2025-09-08 00:34:12 | regressions | 1 | 49908 | 4 | 0.876 | 56972.6 |
843 | 2025-09-07 12:30:17 | regressions | 2 | 86808 | 14 | 4.076 | 21297.4 |
842 | 2025-09-03 13:31:57 | regressions | 1 | 49908 | 4 | 0.763 | 65410.2 |
841 | 2025-09-02 21:50:28 | regressions | 2 | 86808 | 14 | 2.250 | 38581.3 |
840 | 2025-09-02 20:38:20 | regressions | 3 | 121633 | 46 | 4.936 | 24642.0 |
839 | 2025-08-28 17:20:32 | regressions | 1 | 49908 | 4 | 0.890 | 56076.4 |
838 | 2025-08-27 12:05:12 | regressions | 2 | 86808 | 14 | 2.486 | 34918.7 |
837 | 2025-08-25 23:06:46 | regressions | 3 | 121633 | 46 | 8.456 | 14384.2 |
836 | 2025-08-20 23:47:24 | regressions | 3 | 121633 | 46 | 12.596 | 9656.5 |
835 | 2025-08-17 15:03:55 | regressions | 3 | 121633 | 46 | 12.580 | 9668.8 |
834 | 2025-08-17 03:36:03 | regressions | 2 | 86808 | 14 | 5.296 | 16391.2 |
833 | 2025-08-16 06:20:28 | regressions | 1 | 49908 | 4 | 0.873 | 57168.4 |
832 | 2025-08-13 14:29:02 | regressions | 1 | 49908 | 4 | 2.623 | 19027.1 |
831 | 2025-08-13 08:39:11 | regressions | 1 | 49908 | 4 | 0.860 | 58032.6 |
830 | 2025-08-11 22:12:49 | regressions | 1 | 49908 | 4 | 3.780 | 13203.2 |
829 | 2025-08-10 21:00:58 | regressions | 4 | 148819 | 182 | 23.580 | 6311.2 |
828 | 2025-08-10 12:16:19 | regressions | 1 | 49908 | 4 | 4.313 | 11571.5 |
827 | 2025-08-09 12:54:36 | regressions | 4 | 148819 | 182 | 10.190 | 14604.4 |
826 | 2025-08-05 23:39:47 | regressions | 4 | 148819 | 182 | 24.390 | 6101.6 |
825 | 2025-08-03 23:16:45 | regressions | 1 | 49908 | 4 | 2.546 | 19602.5 |
824 | 2025-08-03 01:13:44 | regressions | 4 | 148819 | 182 | 61.536 | 2418.4 |
823 | 2025-07-27 23:14:57 | regressions | 4 | 148819 | 182 | 26.360 | 5645.6 |
822 | 2025-07-27 23:01:57 | regressions | 4 | 148819 | 182 | 27.563 | 5399.2 |
821 | 2025-07-25 03:58:37 | regressions | 1 | 49908 | 4 | 3.920 | 12731.6 |
820 | 2025-07-25 02:11:18 | regressions | 4 | 148819 | 182 | 34.313 | 4337.1 |
819 | 2025-07-25 01:18:35 | regressions | 1 | 49908 | 4 | 5.063 | 9857.4 |
818 | 2025-07-24 02:09:56 | regressions | 1 | 49908 | 4 | 2.826 | 17660.3 |
817 | 2025-07-23 04:38:24 | regressions | 1 | 49908 | 4 | 2.170 | 22999.1 |
816 | 2025-07-22 22:55:25 | regressions | 1 | 49908 | 4 | 2.266 | 22024.7 |
815 | 2025-07-22 21:33:35 | regressions | 1 | 49908 | 4 | 4.283 | 11652.6 |
814 | 2025-07-22 17:02:49 | regressions | 1 | 49908 | 4 | 2.673 | 18671.2 |
813 | 2025-07-22 14:13:23 | regressions | 1 | 49908 | 4 | 2.190 | 22789.0 |
812 | 2025-07-21 04:01:17 | regressions | 1 | 49908 | 4 | 0.906 | 55086.1 |
811 | 2025-07-17 14:54:22 | regressions | 3 | 121633 | 46 | 18.583 | 6545.4 |
810 | 2025-07-16 19:28:44 | regressions | 4 | 148819 | 182 | 11.093 | 13415.6 |
809 | 2025-07-16 00:59:24 | regressions | 1 | 49908 | 4 | 4.390 | 11368.6 |
808 | 2025-07-15 11:08:35 | regressions | 1 | 49908 | 4 | 4.063 | 12283.5 |
807 | 2025-07-12 23:42:16 | regressions | 1 | 49908 | 4 | 1.783 | 27991.0 |
806 | 2025-07-10 15:08:47 | regressions | 1 | 49908 | 4 | 2.830 | 17635.3 |
805 | 2025-07-09 07:00:56 | regressions | 1 | 49908 | 4 | 0.813 | 61387.5 |
804 | 2025-07-02 05:54:34 | regressions | 4 | 148819 | 182 | 26.936 | 5524.9 |
803 | 2025-07-02 00:20:41 | regressions | 1 | 49908 | 4 | 3.080 | 16203.9 |
802 | 2025-07-01 16:30:46 | regressions | 1 | 49908 | 4 | 0.826 | 60421.3 |
801 | 2025-06-27 13:38:00 | regressions | 4 | 148819 | 182 | 48.406 | 3074.4 |
800 | 2025-06-24 16:07:33 | regressions | 1 | 49908 | 4 | 3.343 | 14929.1 |
799 | 2025-06-24 14:54:28 | regressions | 4 | 148819 | 182 | 29.190 | 5098.3 |
798 | 2025-06-22 01:08:00 | regressions | 4 | 148819 | 182 | 29.376 | 5066.0 |
797 | 2025-06-21 07:46:09 | regressions | 1 | 49908 | 4 | 0.856 | 58303.7 |
796 | 2025-06-19 23:27:26 | regressions | 1 | 49908 | 4 | 2.393 | 20855.8 |
795 | 2025-06-18 15:35:39 | regressions | 1 | 49908 | 4 | 4.643 | 10749.1 |
794 | 2025-06-17 00:50:30 | regressions | 4 | 148819 | 182 | 37.453 | 3973.5 |
793 | 2025-06-16 17:07:11 | regressions | 4 | 148819 | 182 | 49.596 | 3000.6 |
792 | 2025-06-15 09:41:40 | regressions | 3 | 121633 | 46 | 5.063 | 24023.9 |
791 | 2025-06-15 07:32:51 | regressions | 4 | 148819 | 182 | 42.406 | 3509.4 |
790 | 2025-06-15 01:26:26 | regressions | 2 | 86808 | 14 | 2.576 | 33698.8 |
789 | 2025-06-13 22:40:11 | regressions | 1 | 49908 | 4 | 4.453 | 11207.7 |
788 | 2025-06-10 21:12:57 | regressions | 1 | 49908 | 4 | 0.970 | 51451.5 |
787 | 2025-06-10 10:17:49 | regressions | 1 | 49908 | 4 | 4.126 | 12096.0 |
786 | 2025-05-19 23:51:23 | regressions | 1 | 49908 | 4 | 3.810 | 13099.2 |
785 | 2025-05-17 22:55:17 | regressions | 2 | 86808 | 14 | 13.046 | 6654.0 |
784 | 2025-05-08 01:08:38 | regressions | 3 | 121633 | 46 | 25.050 | 4855.6 |
783 | 2025-05-07 22:44:22 | regressions | 1 | 49908 | 4 | 3.813 | 13088.9 |
782 | 2025-05-02 00:14:25 | regressions | 1 | 49908 | 4 | 5.640 | 8848.9 |
781 | 2025-05-01 10:42:41 | regressions | 3 | 121633 | 46 | 18.376 | 6619.1 |
780 | 2025-04-26 09:51:26 | regressions | 1 | 49908 | 4 | 2.936 | 16998.6 |
779 | 2025-04-26 03:24:22 | regressions | 1 | 49908 | 4 | 4.580 | 10896.9 |
778 | 2025-04-26 02:32:44 | regressions | 3 | 121633 | 46 | 21.313 | 5707.0 |
777 | 2025-04-21 00:21:13 | regressions | 3 | 121633 | 46 | 25.830 | 4709.0 |
776 | 2025-04-19 22:31:10 | regressions | 1 | 49908 | 4 | 2.296 | 21736.9 |
775 | 2025-04-19 12:09:20 | regressions | 3 | 121633 | 46 | 9.890 | 12298.6 |
774 | 2025-04-05 22:41:51 | regressions | 1 | 49908 | 4 | 4.110 | 12143.1 |
773 | 2025-03-26 23:46:45 | regressions | 1 | 49908 | 4 | 3.063 | 16293.8 |
772 | 2025-03-26 01:07:19 | regressions | 1 | 49908 | 4 | 6.016 | 8295.9 |
771 | 2025-03-25 11:44:32 | regressions | 1 | 49908 | 4 | 6.140 | 8128.3 |
770 | 2025-03-25 10:05:59 | regressions | 2 | 86808 | 14 | 6.343 | 13685.6 |
769 | 2025-03-23 14:53:38 | regressions | 3 | 121633 | 46 | 26.580 | 4576.1 |
768 | 2025-03-21 11:46:15 | regressions | 3 | 121633 | 46 | 38.740 | 3139.7 |
767 | 2025-03-21 08:24:26 | regressions | 4 | 148819 | 182 | 54.160 | 2747.8 |
766 | 2025-03-21 01:38:51 | regressions | 2 | 86808 | 14 | 12.826 | 6768.1 |
765 | 2025-03-19 23:27:17 | regressions | 1 | 49908 | 4 | 1.830 | 27272.1 |
764 | 2025-03-05 20:07:33 | regressions | 1 | 49908 | 4 | 4.283 | 11652.6 |
763 | 2025-02-26 22:45:18 | regressions | 1 | 49908 | 4 | 5.813 | 8585.6 |
762 | 2025-02-23 21:11:02 | regressions | 1 | 49908 | 4 | 5.920 | 8430.4 |
761 | 2025-02-20 13:29:59 | regressions | 3 | 121633 | 46 | 23.893 | 5090.7 |
760 | 2025-02-19 10:25:19 | regressions | 3 | 121633 | 46 | 32.693 | 3720.5 |
759 | 2025-02-18 10:47:53 | regressions | 4 | 148819 | 182 | 57.073 | 2607.5 |
758 | 2025-02-17 16:28:47 | regressions | 3 | 121633 | 46 | 28.626 | 4249.0 |
757 | 2025-02-17 16:28:06 | regressions | 2 | 86808 | 14 | 10.156 | 8547.5 |
756 | 2025-02-16 20:57:49 | regressions | 4 | 148819 | 182 | 49.016 | 3036.1 |
755 | 2025-02-16 16:12:27 | regressions | 4 | 148819 | 182 | 59.363 | 2506.9 |
754 | 2025-02-16 13:46:11 | regressions | 4 | 148819 | 182 | 42.546 | 3497.8 |
753 | 2025-02-16 13:46:08 | regressions | 3 | 121633 | 46 | 27.156 | 4479.0 |
752 | 2025-02-16 13:45:57 | regressions | 2 | 86808 | 14 | 10.906 | 7959.7 |
751 | 2025-02-16 13:41:35 | regressions | 1 | 49908 | 4 | 2.983 | 16730.8 |
750 | 2025-02-15 07:17:23 | regressions | 1 | 49908 | 4 | 2.296 | 21736.9 |
749 | 2025-01-25 01:23:28 | regressions | 4 | 148819 | 182 | 10.330 | 14406.5 |
748 | 2025-01-25 01:04:28 | regressions | 1 | 49908 | 4 | 1.903 | 26226.0 |