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+1
+00:00:00,110 --> 00:00:02,570
+So let me use a slightly expanded version of this
+
+2
+00:00:02,570 --> 00:00:05,560
+grid. Although we're indeed looking at a needle in a haystack.
+
+3
+00:00:05,560 --> 00:00:09,560
+And failing inputs are generally sparse, very sparse, in the input
+
+4
+00:00:09,560 --> 00:00:12,890
+domain. However, they tend to be dense in some parts of
+
+5
+00:00:12,890 --> 00:00:15,860
+the domain. Like here or here. So how can we leverage
+
+6
+00:00:15,860 --> 00:00:18,920
+this? The fact that the failures are dense in some subdomains?
+
+7
+00:00:18,920 --> 00:00:22,290
+As it turns out, the domain is naturally split into partitions.
+
+8
+00:00:22,290 --> 00:00:25,340
+Where partitions are areas of the domain that are treated homogeneously
+
+9
+00:00:25,340 --> 00:00:28,070
+by the software. And this is what happens, that normally,
+
+10
+00:00:28,070 --> 00:00:31,020
+failures tend to be dense in this partitions. So the way
+
+11
+00:00:31,020 --> 00:00:34,000
+to leverage this characteristic of failures, is that we don't know
+
+12
+00:00:34,000 --> 00:00:36,950
+want to pick inputs randomly, in the input domain. Just here
+
+13
+00:00:36,950 --> 00:00:39,460
+and there. Rather we want to do two things. First we
+
+14
+00:00:39,460 --> 00:00:43,300
+want to identify partitions of our domain. And second we want
+
+15
+00:00:43,300 --> 00:00:46,950
+to select inputs from each partition. And by doing so, we
+
+16
+00:00:46,950 --> 00:00:50,300
+can dramatically increase our chances to reveal faults in the code.
+
+17
+00:00:50,300 --> 00:00:54,170
+So the name that is normally used for this process, is partition testing.